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ronaknnathani/relay
Skills to orchestrate coding agents to do long horizon tasks with little to no steering
History
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Individual skills in this repository
- build-write-like-me
skills/build-write-like-me - clarify
skills/clarify - commit
skills/commit - deliver-pr
skills/deliver-pr - explore
skills/explore - implement
skills/implement - open-pr
skills/open-pr - plan
skills/plan - pr-fix
skills/pr-fix - pr-monitor
skills/pr-monitor - rebase
skills/rebase - relay-archive
skills/relay-archive - relay-status
skills/relay-status - review
skills/review - review-pr
skills/review-pr - simplify
skills/simplify - stack-ship
skills/stack-ship - tl
skills/tl - todo
skills/todo - validate
skills/validate - write-like-me
skills/write-like-me
How it works
build-write-like-me
When your agent uses it
Use this skill whenever the user wants to capture, clone, or codify their own (or someone's) writing voice into a reusable skill. Trigger phrases include: "build a write-like-me skill", "build a sound-like-me skill", "analyze how I write", "make agents write or draft in my voice", "learn my style from my docs and PRs", "generate a voice profile from my github", "stop the agent sounding like a robot when it writes for me", "turn my docs and PRs into a personal style guide". It gathers a corpus of the person's real writing (GitHub PRs and comments, docs, blog posts, chat, optional Slack and email), filters out AI-written content, runs stylometric analysis, and synthesizes a reusable voice-profile skill. Prefer this skill over improvising the analysis yourself, because it encodes rate-limit-safe fetching and an agent-content filter you would otherwise get wrong. Do NOT use it to draft or edit a single email, PR, doc, or post, to lint code style, or to define team documentation standards.
What it loads into context
Frontmatter
254 tokensAlways available to the agent
SKILL.md
3,242 tokensWhen the skill is activated
Reference documents
3,805 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- The workflow
- Step 1: Collect sources
- Step 2: Set up the workspace
- Step 3: Gather raw data
- Step 4: Analyze
- Step 5: Synthesize the SKILL.md
- Step 6: Self-consistency check and present
- Bundled resources
- Notes on doing this well
Scripts executed separately
scripts/analyze_style.pyscripts/extract_transcripts.pyscripts/fetch_github.py
Files
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# Write-Like-Me Builder
This skill builds a *personalized* writing-voice skill for one person. The output
is a `SKILL.md` that any agent can load to draft or edit prose in that person's
voice. You produce it by gathering the person's real writing from sources they
provide, analyzing it (both statistically and by reading it), and synthesizing a
profile grounded in real examples.
The core principle: **a voice profile is only as good as the real writing behind
it.** Don't invent traits. Every claim in the generated skill should trace to
something the person actually wrote. Quote them verbatim wherever you can.
## The workflow
View the complete source on GitHubclarify
When your agent uses it
Turn a vague or underspecified task into a crisp requirements + testable acceptance-criteria document by closing the gap between what was asked and what is actually wanted. Use at the start of any non-trivial task before planning, whenever the goal is fuzzy ("make it faster", "make it more robust", "add validation"), or whenever you cannot predict how the user would judge "done". Its output feeds `plan`. (For tidying existing code, use `simplify`, not clarify.)
What it loads into context
Frontmatter
105 tokensAlways available to the agent
SKILL.md
1,582 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Process
- Reject vague delegation
- Output schema (the artifact)
- Red flags
- Verification checklist
Files
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# Clarify
Produce a requirements + acceptance-criteria artifact that pins down what success looks like, so a
planner never has to guess. The bar: every requirement is measurable and every acceptance criterion is
checkable — you could hand the artifact to someone else and they'd build the right thing. This is a
peer phase to `plan`, not its parent: it grounds itself in the code via `explore`, then hands its
artifact to `plan`. It does **not** design the implementation and does **not** invoke `plan`.
## Process
1. **Resolve from the codebase before asking.** If a question's answer is discoverable in the code —
how a thing currently works, what the existing convention is, where an integration point lives —
call `explore` (dispatch a sub-agent when available; otherwise do it inline) and find it. Only ask
the user what you genuinely cannot determine. Bothering them with a discoverable fact erodes trust.View the complete source on GitHubcommit
When your agent uses it
Create a single well-formed git commit from the working changes, following the repo's AGENTS.md and recent commit-message conventions. Use when the caller wants only to commit — not push and not open a PR (for that, use `open-pr`).
What it loads into context
Frontmatter
57 tokensAlways available to the agent
SKILL.md
341 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Gather context
- Create the commit
Files
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# Commit
Create a single git commit for the current changes.
## Gather context
First inspect the working tree. Run these read-only commands and read their output:
- `git status` — what is staged and unstaged
- `git diff HEAD` — the full staged and unstaged diff
- `git branch --show-current` — the current branch
- `git log --oneline -10` — recent commit message style to match
## Create the commitView the complete source on GitHubdeliver-pr
When your agent uses it
Deliver one change end to end as a single pull request — clarify → plan → implement → simplify → review → validate → open-pr — resuming from wherever it left off. Use to take a task from intent to an open, mergeable PR with each phase run as a focused sub-agent. This is the default workflow the binary launches when you create a new project (`relay "<task>"`).
What it loads into context
Frontmatter
86 tokensAlways available to the agent
SKILL.md
3,222 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Session goal
- Managed assignment — before state routing
- Resume-first — always start here
- The phase pipeline
- Per-phase loop (the router contract)
- Phase gates (where judgment applies)
- Delegation contract
- After the PR is open — hand it to the watcher
- Done
- Red flags
- Verification checklist
Files
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# Deliver PR
Drive one change from a task to an open PR by orchestrating the foundation skills, one phase at a time,
with durable resumable state. You are a **router, not a worker**: you read state, dispatch the next
phase as a sub-agent, record the result, and move on. You do not do the phase work yourself, and you
stay context-light — you read digests and state, never file dumps.
## Session goal
In every agent harness, set `/goal` to the user's requested outcome. The `deliver-pr` workflow is the
execution method, not the goal. Keep `task.md`, requirements, and `relay state` as the durable
definition and progress record across resumes.
## Managed assignment — before state routingView the complete source on GitHubexplore
When your agent uses it
Build a verified, read-only understanding of a codebase or a slice of it — entry points, code flow, architecture, module boundaries, dependencies, data flow, build/test systems, and existing patterns. A shared sub-skill that clarify, plan, implement, and review call on demand when they need codebase context; not invoked directly by users. Never edits anything.
What it loads into context
Frontmatter
81 tokensAlways available to the agent
SKILL.md
1,305 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Shared vocabulary
- Process
- Citations and uncertainty
- Essential files (required closing artifact)
- Red flags
- Verification checklist
Files
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# Explore
Build an accurate, cited map of a codebase — or one feature/area within it — so a downstream skill can
act on it. The output is understanding, not change: this skill **observes and reports only and must
never modify a file, run a mutating command, or write anything except its report.** The bar is a map a
reader can trust because every claim is either backed by a `file:line` reference or explicitly flagged
as unverified. Scope to the topic the caller named; do not map the whole repo when asked about a slice.
## Shared vocabulary
Use these terms so downstream skills that act on this map share one language:
- **Interface** — the surface a caller sees (signatures, exported names, public API).
- **Implementation** — the code behind that surface.View the complete source on GitHubimplement
When your agent uses it
Execute an implementation plan (from `plan`) task by task, writing the code and tests and leaving the system green at every step. Use once you have an agreed plan or a clear next slice of work to build. It does not plan and does not open a PR — it turns a plan into working, tested code.
What it loads into context
Frontmatter
71 tokensAlways available to the agent
SKILL.md
1,238 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Process
- When to stop and ask
- Red flags
- Verification checklist
Files
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# Implement
Turn an implementation plan into working, tested code, one thin slice at a time, keeping the build and
existing tests green at every step. The bar: at any moment you could stop and the system is committable
— nothing half-built, nothing red. This phase consumes the artifact from `plan`; it does **not** design
the approach and does **not** open a PR. Decisions in the plan are settled — follow them; if one is
wrong or missing, stop and surface it rather than quietly inventing a different design.
## Process
1. **Load the plan and review it critically.** Read it end to end before touching code. If a task is
ambiguous, a step is missing, or the approach looks wrong, raise it now — don't paper over a gap
mid-implementation. Turn the plan's tasks into an ordered checklist of slices.
2. **Load coding guidance.** Read the repo's `AGENTS.md` when present, then read global guidance fromView the complete source on GitHubopen-pr
When your agent uses it
Stage, commit, push, and open a pull request following the author's repository and AGENTS.md conventions — repo-style commit messages, a prose PR summary, and a Testing Done command list. Use when work is finished and the caller wants it committed and a PR opened. Supports --draft and an optional local review before push.
What it loads into context
Frontmatter
72 tokensAlways available to the agent
SKILL.md
1,216 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Flags
- Process
- PR body conventions
- Red flags
- Verification checklist
Scripts executed separately
scripts/open-pr.sh
Files
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# Open PR
Take finished work from working tree to open pull request: stage specific files, commit with a
repo-style message, push, and open the PR in the author's house style. Read `<repo>/AGENTS.md` and
`~/.config/agents/AGENTS.md` first (repo-specific rules win) and follow those preferences for commit
messages and PR descriptions. Execute git/`gh` operations through this skill's bundled
`scripts/open-pr.sh` helper rather than inlining command sequences in the skill.
## Flags
- `--draft` — open the PR as a draft (`gh pr create --draft`). Default is open (ready for review).
- `--no-review` — skip the optional local review before push.
## ProcessView the complete source on GitHubplan
When your agent uses it
Turn a clarified requirements artifact into a concrete, executable implementation plan — a decisive architecture blueprint and a phased build sequence with exact file paths. Use after requirements are pinned down (e.g. by `clarify`) and before writing code, whenever a multi-step change needs a design and a task breakdown. Its output feeds `implement`.
What it loads into context
Frontmatter
72 tokensAlways available to the agent
SKILL.md
1,349 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Process
- Task template
- Red flags
- Verification checklist
Files
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# Plan
Given a clarified requirements artifact, produce an implementation plan concrete enough that someone
with no prior context could execute it. The bar: exact file paths and names, one committed
architecture decision, and a phased build sequence `implement` consumes step by step — no abstract
advice, no "add appropriate error handling". This is a peer phase: it grounds itself in the code via
`explore`, picks ONE approach and commits, then hands a plan to `implement`. It does **not** clarify
requirements (that's `clarify`, upstream) and does **not** write production code (that's `implement`,
downstream). It does not invoke either.
## Process
1. **Ground in the codebase first.** Read the clarified artifact (`clarify`'s requirements + success
criteria), then call `explore` (dispatch a sub-agent when available; otherwise inline) and consumeView the complete source on GitHubpr-fix
When your agent uses it
Bring a PR to mergeable — fix CI failures, address review comments, and resolve merge conflicts. Runs either from a supplied watcher worklist (delegated mode, one pass) or from its own assessment (direct mode, looping until clear). Use after opening a PR when CI is red, reviewers have left comments, or the branch conflicts with its base.
What it loads into context
Frontmatter
80 tokensAlways available to the agent
SKILL.md
3,230 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Two modes — check your input first
- Quick commands
- Every automated reply — exact marker, visible disclosure, same source
- Process
- Red flags
- Verification checklist
Files
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# PR Fix
Drive a PR to a mergeable state: a green CI, every review comment fixed-and-resolved or
replied-and-flagged, and no merge conflicts with the base. Work the three
fronts — CI, comments, conflicts — and loop until all are clear. Fix root causes, never silence
failures or guess an author's intent. Use `review`'s shared severity vocabulary (Critical / Important /
Suggestion). Run independent investigations as sub-agents when available; otherwise do them inline.
## Two modes — check your input first
**Delegated mode — a caller supplied a watcher worklist.** `pr-monitor` hands you items taken from a
`relay pr watch` digest: each carries `reason`, `source`, `id`, `answers`, `updatedAt`, `body`,
`thread_id`, `path`, `line`, and for checks the `check_name` and `check_run_id`. That worklist is **complete and
authoritative**:View the complete source on GitHubpr-monitor
When your agent uses it
Handle one pull request attention event end to end — read the watcher digest, triage it, delegate the fixing to pr-fix, re-observe the pull request, and exit. Use when the PR watcher wakes you, or run it manually for a one-shot check of an open PR.
What it loads into context
Frontmatter
66 tokensAlways available to the agent
SKILL.md
2,614 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Where the work comes from
- What the digest already decided
- The run
- Under a project workflow
- Guardrails (non-negotiable)
- Red flags
- Verification checklist
Files
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# PR Monitor
Handle **one** pull request attention event, then stop. You are a **router**: the `relay pr watch`
runtime does the observing, you interpret its digest, delegate the fixing to `pr-fix`, re-observe the
pull request, and exit. You never write code, never post in your own voice, never approve, and never
merge.
There is **no acknowledgement**. The watcher never records that attention was handled, because a local
claim can be wrong. Every tick re-reads the live pull request, and an item disappears only when the
remote state itself no longer shows it: the check passes or reruns, the head SHA changes, the conflict
clears, the thread resolves, your reply lands on that exact source, auto-merge is armed, or the pull
request closes or merges. If nothing changed, the problem is still there and it will wake you again —
which is correct.
View the complete source on GitHubrebase
When your agent uses it
Use when you need to rebase the current branch onto main, resolve merge conflicts, and force-push
What it loads into context
Frontmatter
37 tokensAlways available to the agent
SKILL.md
688 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Steps
Files
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# Rebase — Rebase, Fix Conflicts, Push
Rebase the current branch onto the base branch (default: `main`), resolve any merge conflicts, and force-push.
## Steps
### 1. Determine Base Branch
- If `$ARGUMENTS` contains a branch name, use it as the base.
- Otherwise, default to `main`.
### 2. Pre-check Working Tree
```bashView the complete source on GitHubrelay-archive
When your agent uses it
Use when a project's PR is merged and you want to clean up the worktree while preserving notes and plans
What it loads into context
Frontmatter
45 tokensAlways available to the agent
SKILL.md
68 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
Files
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# Relay Archive — Project Archival
```bash
relay archive $ARGUMENTS
```View the complete source on GitHubrelay-status
When your agent uses it
Use when checking the status of active or archived development projects
What it loads into context
Frontmatter
47 tokensAlways available to the agent
SKILL.md
76 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
Files
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# Relay Status — Project Status
Display the status of relay projects.
```bash
relay status $ARGUMENTS
```View the complete source on GitHubreview
When your agent uses it
Review a change for correctness, quality, and guideline compliance using a library of specialized reviewer roles. Use before opening a PR, after finishing a chunk of work, or to review an existing PR. Two output modes — a local severity-ranked report for a fix loop (default), or inline GitHub comments (--comment). Scores every finding for confidence, filters the noise, and delegates each role adversarially.
What it loads into context
Frontmatter
87 tokensAlways available to the agent
SKILL.md
2,383 tokensWhen the skill is activated
Reference documents
6,070 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Modes
- The reviewer-role library
- 1. Scope and the should-review gate
- 2. Pick the applicable roles
- 3. Review along two axes, kept separate
- 4. Delegate each role adversarially (doubt-driven)
- 5. Score every finding 0-100, then filter
- 6. Dedup, validate, description gate
- 7. Emit
- Severity vocabulary (shared with pr-fix and deliver-pr)
- Red flags
- Verification checklist
Files
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# Review
Review a change with a library of specialized reviewer roles, score every finding for confidence,
drop the noise, and emit results in one of two modes. The goal is signal: high-confidence findings a
senior engineer would actually raise, each with a concrete fix — never a wall of nitpicks.
## Modes
- **report** (default) — produce a local, severity-ranked findings report for the author or a fix
loop (e.g. `pr-fix`). Posts nothing.
- **inline** (`--comment`) — post a summary comment plus inline comments on the PR via `gh`.
## The reviewer-role library
View the complete source on GitHubreview-pr
When your agent uses it
Review someone else's pull request (a PR URL or owner/repo#N) and leave a pending (draft) GitHub review in the user's voice, checked against their AGENTS.md with `review` and `simplify` in report mode. Use when asked to review, re-review, or follow up on a pull request the user did not write, including checking whether the author addressed earlier feedback.
What it loads into context
Frontmatter
88 tokensAlways available to the agent
SKILL.md
2,697 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prepare the checkout and state
- Trust boundary
- Process
- Red flags
- Verification checklist
Files
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# Review PR
Review a pull request the user did not write, the way their own generated code gets reviewed, and
leave a **draft** GitHub review they can edit and submit. The bar: every comment is something the
user would raise themselves, in their voice, anchored to the right line, and no earlier finding is
forgotten or raised twice. Never submit, approve, or request changes. The user does.
## Prepare the checkout and state
Bind `$PR` to the pull request the user named (a URL or `<owner>/<repo>#<number>`). If none was
named and the launch context does not name one, ask for it. Then run:
```bash
relay review "$PR" --no-launchView the complete source on GitHubsimplify
When your agent uses it
Reduce complexity in recently changed code — cut needless abstraction, dead code, and duplication; improve names and structure — WITHOUT changing behavior. Quality only; it does not hunt for bugs (use review for that). Use after implementing a chunk of work, before review, or whenever a diff feels more complicated than the problem it solves. Triggers on "clean this up" / "tidy this" / "refactor this" when code already exists; for an underspecified goal with no code yet, use `clarify`.
What it loads into context
Frontmatter
111 tokensAlways available to the agent
SKILL.md
1,363 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Step 0 — the invariant
- Scan — three buckets
- The deletion test
- Two-sided guardrail
- Report mode
- Process
- Red flags
- Verification checklist
Files
SKILL.mdcore6,098 bytes
Read SKILL.md
# Simplify
Make a change simpler and clearer without changing what it does. The bar: readable, explicit code over
clever, compact code — would a senior engineer call this overcomplicated? Scope is the **recently
changed code** — the working diff (e.g. `git diff` against the branch point) unless the caller names
files. This is quality-only: it does not hunt for bugs (that's `review`).
## Step 0 — the invariant
**Preserve functionality. Never change what the code does, only how it does it.** Every original
feature, output, and behavior stays intact. If a simplification would alter behavior, it is a `review`
or implementation concern, not a simplification — stop and surface it.
## Scan — three bucketsView the complete source on GitHubstack-ship
When your agent uses it
Use only for a standalone stack explicitly launched with `relay --workflow stack-ship`; never invoke inside a tech-lead-managed Relay program. Decompose one goal into small PRs, delegate build and monitor work, surface author decisions, and auto-merge only after human approval.
What it loads into context
Frontmatter
72 tokensAlways available to the agent
SKILL.md
2,530 tokensWhen the skill is activated
Reference documents
7,571 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- The one-paragraph model
- When to use / not use
- Operating principles (the orchestrator's contract)
- Workflow
- State files (single source of truth) → [references/state-files.md](references/state-files.md)
- Stacked-PR mechanics → [references/stacked-mechanics.md](references/stacked-mechanics.md)
- Hard guardrails → [references/guardrails.md](references/guardrails.md)
Files
SKILL.mdcore10,701 bytesSKILL.mdcore10,701 bytesSKILL.mdcore10,701 bytesSKILL.mdcore10,701 bytesreferences/decomposition.mddoc5,572 bytesreferences/guardrails.mddoc7,066 bytesreferences/monitor-loop.mddoc3,829 bytesreferences/pr-build-cycle.mddoc3,087 bytesreferences/stacked-mechanics.mddoc4,716 bytesreferences/state-files.mddoc6,662 bytes
Read SKILL.md
# Stack Ship
Drive a design or feature goal from intake to "all PRs merged" with **near-zero steering**. The
orchestrator is a **router, not a worker**: it owns the plan, state, delegation, and author-facing
decisions; subagents own execution and return structured digests.
The [guardrails](references/guardrails.md) are non-negotiable — **read them before acting.**
> Throughout this skill `master` denotes the repository's **default branch**; substitute the real
> default (`main`, etc.). Auto-merge is armed only on a default-branch-based PR — which, in a stack, is
> exactly the front PR.
## The one-paragraph model
View the complete source on GitHubtl
When your agent uses it
Manage a Relay program as the CEO-facing tech lead: shape goals and contracts, prioritize dependency-aware work, dispatch senior worker agents, and surface every decision without writing production code or merging.
What it loads into context
Frontmatter
44 tokensAlways available to the agent
SKILL.md
5,633 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Resume first
- Adaptive patrol
- Changes the CEO asks for on an open pull request
- Retiring merged work
- Operating model
- Process
- Explicit QA in V1
- Red flags
- Verification checklist
Files
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Read SKILL.md
# Tech lead
Act as the single CEO-facing engineering leader for one Relay program. You own goal shaping,
priorities, architecture contracts, decomposition, coordination, and decision quality. Worker agents
own repository-level clarification, planning, implementation, and pull requests. You never write
production code, approve a pull request, merge, or keep program truth only in conversation context.
## Resume first
`<slug>` is the argument passed to this skill. Bind it to `$PROGRAM`.
Managed programs run only under Herdr. Every managed command—`program new`, `program resume`,
`program dispatch`, `program worker start`, `patrol start`, `patrol run`, and a managed child's
`relay resume`—verifies the `herdr` binary, the owning Herdr pane, and a reachable Herdr serverView the complete source on GitHubtodo
When your agent uses it
Capture, list, and complete repo-scoped todos
What it loads into context
Frontmatter
39 tokensAlways available to the agent
SKILL.md
151 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Dispatch
Files
SKILL.mdcore615 bytes
Read SKILL.md
# /todo — Repo-Scoped Todos
Capture todos from within a session for later pickup. Runs as a sub-agent to keep the main session context clean.
## Dispatch
{{subagent:fast}} with this prompt:
> Run the following shell command and report the output exactly as printed:
>
> ```bash
> relay todo $ARGUMENTS
> ```
>View the complete source on GitHubvalidate
When your agent uses it
Verify a change is ready to ship by checking it against its acceptance criteria and running the repo's own quality gates in order, then report a pass/fail verdict with the exact failures. Use to decide go/no-go right before shipping — when you want a pass/fail verdict against acceptance criteria and the repo's quality gates (lint/build/test), not a code critique (use `review` for that). It reports — it does not fix (route failures to `pr-fix`/`implement`) and does not ship.
What it loads into context
Frontmatter
112 tokensAlways available to the agent
SKILL.md
1,246 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Process
- Never mask a failure to go green
- Output schema (the verdict)
- Red flags
- Verification checklist
Files
SKILL.mdcore5,266 bytes
Read SKILL.md
# Validate
Decide whether a change is ready to ship and report the verdict — pass, or fail with the exact
failures someone else can act on. The bar: every acceptance criterion from `clarify`/`plan` is
demonstrably met, and every quality gate the repo defines is green, each shown by a command or
observation rather than asserted. This skill is a gate, not a fixer: on failure it hands precise
error-feedback to `pr-fix` or `implement` and stops. It does **not** edit code and does **not** ship.
## Process
1. **Gather the acceptance criteria.** Read the Success criteria from the `clarify`/`plan` artifacts.
These are the goal-backward targets — what must be TRUE about the codebase. If no artifact exists,
reconstruct the criteria from the task description and list them, so the verdict is checkable.
2. **Discover the repo's own gate commands.** Find how *this* repo lints, type-checks, tests, builds,View the complete source on GitHubwrite-like-me
When your agent uses it
Write or edit prose in author's voice, or check that a draft sounds like them. Use for blog posts, design and strategy docs, PR descriptions, commits and review comments, chat / agent instructions, peer feedback, or any first-person writing on their behalf, and whenever an agent is producing text that will go out under their name and needs to sound like them, not like a generated reply.
What it loads into context
Frontmatter
97 tokensAlways available to the agent
SKILL.md
4,111 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Voice in one paragraph
- Non-negotiable mechanics
- Pick the register first
- The moves that make it sound like you
- Register playbooks (with examples)
- Signature phrases
- What to strip (the slop tells)
- When editing (not drafting)
- Pre-send checklist
Files
SKILL.mdcore17,271 bytes
Read SKILL.md
# Write Like Ronak
You are writing as Ronak. The goal is prose indistinguishable from what he'd
write himself. This guide tells you how. When in doubt, be plainer, shorter, and
more concrete than your default.
## Voice in one paragraph
Direct, concrete, unceremonious. Lead with the point in the first sentence.
Prefer short declarative sentences, one idea each. Say the *why* right after the
*what*. Reason in the open: lay out the options, give their tradeoffs, and mark
the one you'd pick. Often make a point by asking a question instead of asserting.
Stay collaborative ("we", "let's") even when disagreeing. Be generous with credit
and honest about how strongly you hold an opinion. Use plain words: no hype, noView the complete source on GitHubSkills included
- build-write-like-me
- clarify
- commit
- deliver-pr
- explore
- implement
- open-pr
- plan
- pr-fix
- pr-monitor
- rebase
- relay-archive
- relay-status
- review
- review-pr
- simplify
- stack-ship
- tl
- todo
- validate
- write-like-me
Repository facts
- License
- MIT
- Created
- Jun 17, 2026
- Last pushed
- Nov 5, 2026
- Forks
- 4
- Open issues
- 0
- Project activity
- Active
Before you install
Network or broad shellAutomated signals, not a guarantee
Checked Nov 5, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 57 notes
skills/build-write-like-me/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/build-write-like-me/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/build-write-like-me/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/build-write-like-me/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/build-write-like-me/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/build-write-like-me/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/build-write-like-me/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/build-write-like-me/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/build-write-like-me/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/build-write-like-me/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/deliver-pr/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/deliver-pr/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/deliver-pr/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/deliver-pr/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/pr-fix/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/pr-fix/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/pr-fix/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/pr-fix/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/pr-fix/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/pr-fix/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- No broad tool permissions
- No dangerous shell commands
- 3 network referencesin 2 files: build-write-like-me/references/source-gathering.md:55 build-write-like-me/SKILL.md:71
- No hidden or obfuscated text
- No instruction overrides
- 4 executable scriptsin 4 files: build-write-like-me/scripts/analyze_style.py:1 build-write-like-me/scripts/extract_transcripts.py:1 build-write-like-me/scripts/fetch_github.py:1 and 1 more
- No access to secrets
- No requests to vote in Hot
Show all 7 signals by file
skills/build-write-like-me/SKILL.md
- Network accessline 71
Sources that need a tool to fetch (Google Docs, Slack, email, GitHub) are only
skills/build-write-like-me/references/source-gathering.md
skills/build-write-like-me/scripts/analyze_style.py
- Executable scriptline 1
#!/usr/bin/env python3
skills/build-write-like-me/scripts/extract_transcripts.py
- Executable scriptline 1
#!/usr/bin/env python3
skills/build-write-like-me/scripts/fetch_github.py
- Executable scriptline 1
#!/usr/bin/env python3
skills/open-pr/scripts/open-pr.sh
- Executable scriptline 1
#!/usr/bin/env bash
How the signals fit together
Facts from a static read of the files at the pinned commit. They describe what the code does, not why.
Some files could not be read; the facts below still hold.
Signal confidence: 7 facts
- Network access in prose of the SKILL.mdbuild-write-like-me/SKILL.md:71Low confidence
- Network access in prose of documentationbuild-write-like-me/references/source-gathering.md:55Low confidence
- Network access in prose of documentationbuild-write-like-me/references/source-gathering.md:57Low confidence
- Executable script in code of a file that runsbuild-write-like-me/scripts/analyze_style.py:1High confidence
- Executable script in code of a file that runsbuild-write-like-me/scripts/extract_transcripts.py:1High confidence
- Executable script in code of a file that runsbuild-write-like-me/scripts/fetch_github.py:1High confidence
- Executable script in code of a file that runsopen-pr/scripts/open-pr.sh:1High confidence
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Native | Frontmatter field argument-hint in skills/rebase/SKILL.md | .claude/skills/<skill-name>/ |
| Codex | Compatible | Standard SKILL.md skills/build-write-like-me/SKILL.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md skills/build-write-like-me/SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md skills/build-write-like-me/SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md skills/build-write-like-me/SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md skills/build-write-like-me/SKILL.md | .opencode/skills/<skill-name>/ |
- Native The repository ships a manifest, folder or frontmatter field for this agent.
- Compatible A standard SKILL.md that this agent can read.
- Unknown No evidence either way.
Derived automatically from paths, manifests and frontmatter. Not tested on each agent.