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dreamers-laboratory/agent-fleet-manager

A general-purpose engine for large-scale, repeated information gathering by a fleet of workers.

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1skill in this repository
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Oct 25, 2026Nov 5, 2026139

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Individual skills in this repository

How it works

agent-fleet-manager

When your agent uses it

Operate an agentfleet fleet for large-scale periodic information gathering. Use when the user wants to monitor many sources on a schedule (prospect signals, competitor pages, regulatory updates, listings, datasets), act as a worker executing leased batches, review what changed or failed across the fleet, or export fleet activity as OpenTelemetry traces.

What it loads into context

Frontmatter

75 tokens

Always available to the agent

SKILL.md

861 tokens

When the skill is activated

Reference documents

2,059 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

  1. Register what to watch
  2. Run a sweep
  3. Act as a worker yourself
  4. Optional Jev evaluation
  5. Review the fleet
  6. Export telemetry

Scripts executed separately

  • agentfleet/__init__.py
  • agentfleet/cli.py
  • agentfleet/engine.py
  • agentfleet/jev.py
  • agentfleet/otel.py
  • examples/demo.py
  • tests/test_engine.py
  • tests/test_jev.py

Files

  • .gitignoreasset62 bytes
  • CHANGELOG.mddoc834 bytes
  • LICENSEasset11,358 bytes
  • README.mddoc8,268 bytes
  • SKILL.mdcore3,719 bytes
  • SKILL.mdcore3,719 bytes
  • SKILL.mdcore3,719 bytes
  • agentfleet/__init__.pyruns155 bytes
  • agentfleet/cli.pyruns5,975 bytes
  • agentfleet/engine.pyruns10,061 bytes
  • agentfleet/jev.pyruns8,801 bytes
  • agentfleet/otel.pyruns3,838 bytes
  • agentfleet/schema.sqlasset2,541 bytes
  • examples/demo.pyruns2,042 bytes
  • examples/jev_questions.jsonasset420 bytes
  • examples/jev_request.jsonasset525 bytes
  • tests/test_engine.pyruns4,077 bytes
  • tests/test_jev.pyruns12,697 bytes
Read SKILL.md

# Operating an agentfleet fleet

One SQLite file holds the whole fleet. All commands take `--db <path>`. Full mechanics are in [README.md](README.md); this file is the operating procedure.

## Register what to watch

```
python -m agentfleet.cli add-source --db fleet.db <name> <route> --cadence <seconds>
```

The route means whatever your worker decides: a URL for the built-in HTTP fetcher, a search query, an API endpoint, a natural-language instruction for an agent worker. Pick cadences honestly — a careers page is an hourly-to-daily source; a statute database is weekly. Do not register sources the user has no right to fetch, and respect robots.txt and rate expectations when the worker is a fetcher you control.

## Run a sweep
View the complete source on GitHub

Skills included

  • agent-fleet-manager

Repository facts

License
Apache-2.0
Created
Sep 2, 2026
Last pushed
Oct 1, 2026
Forks
0
Open issues
0
Project activity
Active

Before you install

Network or broad shell

Automated 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 2 notes
  • SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
  • SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
Show all 52 signals by file

.gitignore

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LICENSE

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    Apache License                            Version 2.0, January 2004                         http://www.apache.org/licenses/
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    http://www.apache.org/licenses/
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    http://www.apache.org/licenses/LICENSE-2.0

README.md

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    - **Competitor and price watch.** Pricing pages, feature pages, changelogs, app-store listings — checked on cadence, with `changed` flags you can alert on and history you can chart. - **Regulatory and compliance tracking.** Agency pages, st
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    - **Regulatory and compliance tracking.** Agency pages, statute databases, published guidance. The hash ledger doubles as evidence of when a change appeared and when you saw it. - **Research corpus upkeep.** Datasets, preprint feeds, docume
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    - **Research corpus upkeep.** Datasets, preprint feeds, documentation sets that must stay current. Re-ingest is safe because everything is idempotent by hash. Research-tool example: [alphaXiv](https://x.com/askalphaxiv/status/20947979329941
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    python -m agentfleet.cli add-source --db fleet.db acme-careers https://example.com/careers --cadence 3600
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    Use [TypeSafe's direct API](https://docs.typesafe.ai/api) to classify fetched text or explicit structured state. No SDK, gateway, database migration or key is needed for normal fleet operation. Jev is disabled unless requested.
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    python -m agentfleet.cli export-otel --db fleet.db --endpoint http://localhost:4318
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    Apache-2.0. Built by [Dreamers Inc](https://thedreamers.us).

SKILL.md

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agentfleet/__init__.py

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    Executable file

agentfleet/cli.py

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    python -m agentfleet.cli init --db fleet.db     python -m agentfleet.cli add-source --db fleet.db docs https://example.com/docs --cadence 3600
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    python -m agentfleet.cli add-source --db fleet.db docs https://example.com/docs --cadence 3600
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    python -m agentfleet.cli sweep --db fleet.db --scopes ./scopes     python -m agentfleet.cli status --db fleet.db     python -m agentfleet.cli export-otel --db fleet.db [--endpoint http://localhost:4318]
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    python -m agentfleet.cli status --db fleet.db     python -m agentfleet.cli export-otel --db fleet.db [--endpoint http://localhost:4318] """
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    python -m agentfleet.cli export-otel --db fleet.db [--endpoint http://localhost:4318]
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    def http_executor(route: str):     with urllib.request.urlopen(route, timeout=30) as resp:
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    with urllib.request.urlopen(route, timeout=30) as resp:

agentfleet/engine.py

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agentfleet/jev.py

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    ENDPOINT = "https://api.typesafe.ai/v1/systemone"
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    if self._api_key.encode() in data:             raise JevError("request contains the API credential; refusing to send")         request = urllib.request.Request(ENDPOINT, data=data, headers={
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    request = urllib.request.Request(ENDPOINT, data=data, headers={

agentfleet/otel.py

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    n_spans = len(payload["resourceSpans"][0]["scopeSpans"][0]["spans"])     if endpoint:         req = urllib.request.Request(
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    if endpoint:         req = urllib.request.Request(             endpoint.rstrip("/") + "/v1/traces",
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    req = urllib.request.Request(
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    headers={"Content-Type": "application/json"},         )         with urllib.request.urlopen(req) as resp:
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    )         with urllib.request.urlopen(req) as resp:             resp.read()
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    with urllib.request.urlopen(req) as resp:

examples/demo.py

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    n = len(payload["resourceSpans"][0]["scopeSpans"][0]["spans"])     print(f"\notel export: {n} spans ready for a collector "           f"(pipe to Grafana with export-otel --endpoint http://localhost:4318)")
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    f"(pipe to Grafana with export-otel --endpoint http://localhost:4318)")

tests/test_engine.py

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tests/test_jev.py

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    self.assertEqual(str(caught.exception), f"TypeSafe HTTP {code}; request not completed")             self.opener.open.assert_called_once()         self.assertIsNone(jev._NoRedirect().redirect_request(None, None, 302, "", {}, "https://untrust
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    self.assertIsNone(jev._NoRedirect().redirect_request(None, None, 302, "", {}, "https://untrusted.invalid"))
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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: 48 facts

Works with

Agent compatibility, from the files in this repository
AgentStatusEvidenceInstall to
Claude CodeCompatibleStandard SKILL.md SKILL.md.claude/skills/<skill-name>/
CodexCompatibleStandard SKILL.md SKILL.md.agents/skills/<skill-name>/
CursorCompatibleStandard SKILL.md SKILL.md.cursor/skills/<skill-name>/
Gemini CLICompatibleStandard SKILL.md SKILL.md.gemini/skills/<skill-name>/
GitHub CopilotCompatibleStandard SKILL.md SKILL.md.github/skills/<skill-name>/
OpenCodeCompatibleStandard SKILL.md 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.