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/skill-writer

@5a64b36 official
by Sentrygetsentry/skills1k stars
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Create, synthesize, and iteratively improve agent skills following the Agent Skills specification. Use when asked to "create a skill", "write a skill", "synthesize sources into a skill", "improve a skill from positive/negative examples", "update a skill", or "maintain skill docs and registration". Handles source capture, precision passes, authoring, registration, and validation.

Use this Skill: https://skilld.dev/gh/getsentry/skills/skill-writer

This session only. Nothing lands on disk.

referencesexample-workflow-process-skill.md

≈626 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Case Study: Workflow/Process Skill Synthesis

Scenario

Goal: create a skill for repeatable operational workflows (for example PR prep, CI triage, branching, settings audit).

Input collection approach

This case collected process truth from all authoritative locations:

  1. Official tool docs and syntax references.
  2. Repository workflow conventions and policy docs.
  3. Existing local skills with adjacent process logic.
  4. CI logs, failure patterns, and known operational pitfalls.
  5. Positive and negative historical examples from prior runs.

Collection stopped only after failure and recovery paths were well represented.

Coverage matrix used

Required dimensions tracked during synthesis:

  1. Preconditions and required context.
  2. Ordered execution flow.
  3. Safety/permission boundaries.
  4. Expected outputs and acceptance checks.
  5. Failure handling and retry behavior.
  6. Escalation and handoff behavior.

Synthesized artifacts produced

The resulting skill references included:

  1. Happy-path execution transcript.
  2. Guarded variant with stricter safety constraints.
  3. Failure-recovery transcript for a critical broken step.
  4. Output template for deterministic reporting.
  5. Changelog rules for iterative improvement from examples.

Source-to-decision trace (sample)

  1. Source class: repo policy docs. Decision: add explicit precondition checks before running side-effecting steps. Why: prevented invalid execution in partially configured environments.
  2. Source class: CI failure logs. Decision: add a mandatory failure triage branch with retry vs escalate criteria. Why: reduced dead-end loops during workflow execution.
  3. Source class: historical positive/negative examples. Decision: standardize output format for easier review and iteration. Why: made regressions and improvements comparable across runs.

Concrete artifacts (sample)

  1. Happy-path transcript snippet: Preconditions pass -> execute steps 1..N -> emit structured summary with status per step.
  2. Failure-recovery transcript snippet: Step fails -> classify transient/permanent -> retry once or escalate with captured evidence.
  3. Deterministic report template: Sections: Preconditions, Actions Taken, Validation Results, Failures/Recoveries, Next Actions.

What made this high quality

  1. The workflow was executable without rediscovering steps.
  2. Non-happy paths were first-class, not afterthoughts.
  3. Outputs were structured for consistent review and iteration.

Source: SKILL.md on GitHub

No alerts17d5 checks · Risk SAFE
  • Gen Agent Trust Hub17d

    The skill is a comprehensive meta-router and workflow guide for creating, updating, and evaluating agent skills. It includes a helper python script for structural validation and standard markdown templates, presenting no security risks.

  • Socket17d

    No alerts

  • Snyk17d

    Risk: LOW · No issues

  • Runlayer7mo

    5/19 files flagged

  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

Signed by skilld at 5a64b36. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 3 months ago
  • Documentation
  • skill-authoring
  • workflow
  • specification
  • synthesis
  • iteration
  • validation
  • prompt-engineering
  • agent-skills

README badge

README badge for getsentry/skills/skill-writer

Guides AI agents through a structured workflow for creating, updating, and iterating on agent skills—instruction files that extend AI coding capabilities. Includes reference files for synthesis, authoring, validation, and skill registration following the Agent Skills specification.

Generated from the current SKILL.md.

Does this skill help me write skills for Claude, or does it help Claude write skills?
This skill is loaded into Claude or another AI coding agent. It provides the agent with a standardized workflow, reference files, and decision trees for creating, updating, and iterating on skills that other agents can use.
What's the difference between create, update, synthesize, and iterate modes?
Create starts from scratch. Update modifies an existing skill. Synthesize gathers and structures source material before authoring. Iterate improves a skill based on positive, negative, or fix examples.
Do I need to read all the reference files?
No. The skill uses a step-by-step workflow that loads only the specific reference files needed for your operation. Start with mode-selection.md to determine your path, then load only the files it directs you to.
Can I use this skill to write skills for other AI providers, or only Claude?
The skill supports both provider-agnostic skills and Claude-specific mechanics. Provider-specific references are optional; the core workflow and execution shapes are portable across agents.
What does a completed skill output look like?
A skill consists of a SKILL.md file (the runtime router), optional focused reference files under references/, a SPEC.md for the maintenance contract, and optional scripts or templates. The skill-writer guides you through all artifact types and decides what belongs in each.

Generated from the current SKILL.md. These answers refresh after source changes.