Individual skill
sharpen
Sharpen a task before starting: the expert approach, what the user is really after, and the right level of specification. Use for /sharpen, /pstack:sharpen in Claude Code, or $pstack:sharpen in Codex.
plugins/pstack/skills/sharpen/SKILL.md
Source commit a80f632878066f0291db9e583e76daf09702d303
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Instructions only
- Last checked
- Nov 5, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 16
- Repository last updated
- Nov 4, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- claude-code Repository topic
- codex Repository topic
- cursor Repository topic
- devin Repository topic
- pstack Repository topic
- agent-orchestration Repository topic
- agent-skills Repository topic
- antigravity Repository topic
- claude-code-plugin Repository topic
- claude-code-skills Repository topic
- engineering Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 1,357 bytesagents/openai.yamlasset · 43 bytes
Read excerpt
Before starting, ask:
1. What would a top expert in this field do here that the task does not ask for?
2. What are the rawest sources they would start from instead of what is already digested?
3. Which specific methods and tools would they use?
4. What, other than the agent or the user, would show the result is right?
Ask also what the user is really after, and whether the task is over- or underspecified. Loosen constraints that don't serve the goal as readily as you add ones that do, and leave choices that are the user's to make open instead of deciding them. Fold in only what makes the work better, not bigger, but always keep one outside check that the result is right, without narrating the framing, then do the work. Rewrite the prompt instead only when the user asks for a rewritten prompt.
Invoke manually in either host. Do not load it implicitly. Preserve explicit user constraints, authorization gates, saved model assignments and spending policy. Loosening a constraint that the user chose requires their agreement; do not treat it as an implementation convenience.