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getsentry/skill-writer

getsentry

skill-writer

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.

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New~2.5k
v1.0Saved Jul 11, 2026

Skill Writer

Use this as the single canonical workflow for skill creation and improvement. Primary success condition: maximize high-value input coverage before authoring while minimizing wasted runtime tokens.

Follow the workflow steps in order. Load only the reference files required for the step you are on. SKILL.md is the primary router: every bundled reference file should be flat under references/ and listed here with a direct "open when..." reason.

Core Workflow References

Open when you need to... Read
choose the minimum workflow path for create, update, iterate, or research-first work references/mode-selection.md
choose the simplest adequate execution shape before deciding files references/execution-shapes.md
apply writing constraints for depth, concision, and portability references/design-principles.md
decide what belongs in SKILL.md, references/, SPEC.md, or supporting files references/reference-architecture.md
create or update the maintenance contract for a skill references/spec-template.md
find missing high-signal sources, including history and regressions references/source-discovery.md
adapt an upstream prompt, workflow, rubric, benchmark, or docs into a skill references/source-adaptation.md
run the full synthesis pass with coverage checks and source capture references/synthesis-path.md
author or update SKILL.md, SPEC.md, and supporting files references/authoring-path.md
improve trigger language and false-positive/false-negative behavior references/description-optimization.md
iterate from positive, negative, or fix examples references/iteration-path.md
store persistent working and holdout examples for future revisions references/iteration-evidence.md
choose a response template, schema, or output contract references/output-contracts.md
add or update evals for a skill's generated outputs or runtime behavior references/skill-evals.md
troubleshoot overloaded layouts, hidden refs, or other structure failures references/structure-troubleshooting.md
register the skill and run final validation checks references/registration-validation.md

Artifact Layout References

Open when you need to... Read
keep the whole skill inline in one coherent SKILL.md references/layout-inline-skill.md
split optional deep knowledge into focused routed references references/layout-reference-backed-skill.md
add scripts for deterministic automation or validation references/layout-script-backed-workflow.md
define a skill that is usually invoked with explicit arguments references/layout-argument-driven-skill.md
ship reusable templates, schemas, or other static assets references/layout-asset-template-skill.md

Workflow Mechanic References

Open when you need to... Read
break a task into fixed ordered steps references/workflow-prompt-chaining.md
classify requests and route them to different downstream paths references/workflow-routing.md
split independent work into parallel units or votes references/workflow-parallel.md
discover work units dynamically and coordinate worker outputs references/workflow-orchestrator-workers.md
run validate-fix-repeat checks during authoring or execution references/workflow-validation-loops.md
validate a plan before executing a risky action references/workflow-plan-validate-execute.md

Claude Code References

Open when you need to... Read
use Claude-specific frontmatter or invocation controls references/claude-frontmatter-invocation.md
use Claude argument fields or substitution variables references/claude-argument-substitutions.md
build a skill that runs in isolated context: fork references/claude-subagent-fork.md
build a skill that uses Claude hooks for deterministic enforcement references/claude-hook-backed.md
use Claude shell preprocessing for dynamic context injection references/claude-dynamic-context.md

Example Profiles

Open when you need to... Read
see the expected depth for a documentation-heavy skill references/example-documentation-skill.md
see the expected depth for a workflow-process skill references/example-workflow-process-skill.md
see what a good routed skill looks like references/example-router-skill.md
see what a good subagent-fork skill looks like references/example-subagent-fork-skill.md
see what a good hook-backed skill looks like references/example-hook-backed-skill.md

Step 1: Resolve target, path, and shape

  1. Resolve the intended operation (create, update, synthesize, iterate) and inspect workspace prior art before choosing where files belong.
  2. Choose the target skill root from observed conventions. If the canonical location is still unclear after inspection, ask one direct question before editing files.
  3. Read references/mode-selection.md to choose the minimum required workflow paths.
  4. Read references/execution-shapes.md to choose the primary execution shape.
  5. Default to the simplest adequate shape. If selecting a more complex shape, record why simpler shapes were rejected.
  6. Load only the exact artifact-layout, workflow-mechanic, and provider-specific leaf files required by that shape.
  7. Before adding guidance, identify what existing rule, section, or file should be narrowed, replaced, or removed.
  8. Record portability implications before using provider-specific mechanics.

Step 2: Run synthesis when needed

Read references/synthesis-path.md.

  1. Use this path for new skills, material changes, and research-first planning.
  2. Collect and score relevant sources with provenance.
  3. Read references/source-discovery.md when source material is thin, stale, or ambiguous.
  4. Read references/source-adaptation.md when adapting an upstream prompt, workflow, rubric, benchmark, or docs.
  5. Produce source-backed decisions and coverage/gap status, including the class and execution-shape choice.
  6. Load example profiles only when they add concrete depth for the selected class or shape.
  7. If the skill uses provider-specific mechanics, include current official provider docs and capture usage constraints.
  8. Do not move to authoring until required coverage is understood or gaps are explicit.

Step 3: Run iteration first when improving from outcomes/examples

Read references/iteration-path.md first when selected path includes iteration (for example operation iterate).

  1. Capture and anonymize examples with provenance.
  2. Read references/iteration-evidence.md when examples should persist beyond the current turn.
  3. Review skill behavior against working and holdout slices.
  4. Propose improvements from positive/negative/fix evidence.
  5. Carry concrete behavior deltas into authoring.

Skip this step when selected path does not include iteration.

Step 4: Author or update skill artifacts

Read references/authoring-path.md.

  1. Write or update SKILL.md in imperative voice with trigger-rich description.
  2. Keep SKILL.md as the runtime router, not an encyclopedia.
  3. Run the pre-edit precision check in references/authoring-path.md before creating new sections or files.
  4. Read references/reference-architecture.md before adding bulk instructions or new reference files.
  5. Create or update SPEC.md using references/spec-template.md when creating a new skill or materially changing its contract.
  6. Create focused reference files, scripts, and assets only when each one has a clear "open when..." reason and cannot be handled by tightening an existing file.
  7. If you add a bundled reference file, add a direct routing entry for it in this SKILL.md.
  8. Prefer checklists, tables, templates, and input/output examples over explanatory prose.
  9. Follow only the specific artifact-layout, workflow-mechanic, Claude-specific, and output-contract references selected for this skill.
  10. For advanced execution shapes, add the required routing, delegation, or safety contracts before considering the skill complete.
  11. For authoring/generator skills, include transformed examples in references:
  • happy-path
  • secure/robust variant
  • anti-pattern + corrected version
  1. Read references/skill-evals.md when the request asks for evals, regression cases, benchmark cases, or model-graded quality checks for the skill being authored.
  2. After any skill artifact changes, run the post-change precision pass in references/authoring-path.md before description optimization or validation.

Step 5: Optimize description quality

Read references/description-optimization.md.

  1. Validate should-trigger and should-not-trigger query sets.
  2. Reduce false positives and false negatives with targeted description edits.
  3. Keep trigger language generic across providers unless the skill is intentionally provider-specific.

Step 6: Register and validate

Read references/registration-validation.md.

  1. Apply repository registration steps for the active layout you verified in the workspace.
  2. Run quick validation for structural checks.
  3. Review validator warnings, precision-pass results, and coverage gaps with judgment before completion.

Output format

Return:

  1. Summary
  2. Changes Made
  3. Validation Results
  4. Open Gaps
Files46
46 files · 126.7 KB

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Overall Score

90/100

Grade

A

Excellent

Safety

92

Quality

88

Clarity

91

Completeness

87

Summary

This is a **meta-skill for AI agent skill authoring**, designed to guide agents through creating, synthesizing, updating, and iteratively improving reusable agent skills that conform to the Agent Skills specification. The skill acts as a canonical workflow router that forces high-value source coverage, explicit provenance, focused runtime instructions, and validation before completion. It covers execution-shape selection (inline, reference-backed, script-backed, routing, subagent-fork, hook-backed, etc.), synthesis passes, source discovery, evidence-based iteration, skill authoring with precision checks, and lightweight validation. The skill is comprehensive, well-structured, and includes bundled reference files for each decision point, detailed specifications, examples, evaluation guidance, and validator scripts.

Static Analysis Findings

2 findings

Patterns detected by deterministic static analysis before AI scoring. Hover over any finding code for detailed information and remediation guidance.

Credential Exposure
SEC-020Direct .env File Access

Direct .env file access

references/claude-hook-backed.md.env
Command Injection
SEC-011Dynamic Shell Eval

Shell eval/exec of dynamic content

references/skill-evals.mdexec`

Detected Capabilities

file readfile writedirectory creationscript execution (Python validation)YAML parsinggit operations (implied in setup and validation)structured output analysis

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

create a skillwrite a new skillsynthesize sources into skillimprove skill from examplesupdate skill documentationchoose skill execution shaperegister agent skillauthor skill SPECskill evaluation setupskill source discovery

Risk Signals

INFO

Direct .env file access mentioned in `references/claude-hook-backed.md`

references/claude-hook-backed.md | Match: '.env'
INFO

Shell eval/exec of dynamic content mentioned in `references/skill-evals.md`

references/skill-evals.md | Match: 'exec'

Referenced Domains

External domains referenced in skill content, detected by static analysis.

agentskills.ioaxis.runcacm.acm.orgcode.claude.comdevelopers.openai.comdiataxis.frdita-lang.orggithub.comhuggingface.coopenai.comopenai.github.ioplatform.openai.comwww.anthropic.comwww.apache.orgwww.promptfoo.devwww.writethedocs.org

Use Cases

  • Create a new agent skill from scratch or from external sources
  • Synthesize skill guidance from multiple documentation sources or upstream prompts
  • Update or improve an existing skill based on positive or negative examples
  • Choose the simplest adequate execution shape (inline vs. reference-backed vs. routing, etc.) for a skill before authoring
  • Register a new skill in a repository and run structural validation
  • Author or improve skill evals using AXIS with Codex as the agent under test
  • Decide where to place skill artifacts (SKILL.md, SPEC.md, references/, scripts/, assets/) based on lookup needs and portability
  • Document skill maintenance contracts, source provenance, and evidence models in SPEC.md and SOURCES.md

Quality Notes

  • Exceptional reference architecture: flat, routed-by-lookup-need design with direct 'open when...' entries from SKILL.md prevents overloaded documentation and ensures conditional loading
  • Comprehensive execution-shape decision framework with clear simplicity-first defaults and explicit rejection criteria for advanced mechanics
  • Well-grounded source guidance: traces decisions to provenance, emphasizes commit-history and operational evidence alongside official docs, includes source-adaptation heuristics for upstream material
  • Strong precision-pass discipline: pre-edit and post-change checklists force authors to narrow existing guidance before adding new guidance
  • Excellent meta-router design: separates skill-class selection (what domain), execution-shape selection (how to run), and path selection (which workflows) before authoring begins
  • Detailed provider-specific guidance for Claude Code with explicit portability notes for skills intended to be portable across agents
  • Evaluation framework prescribes AXIS with Codex as harness, separating maintainer evals from runtime skill documentation and emphasizing baseline comparison over one-off scores
  • References include concrete rubrics, decision tables, and checklists rather than prose-heavy guidance
  • SPEC.md template and maintenance specification ensure new skills document intent, scope, evidence model, and known limitations upfront
  • Supporting scripts (quick_validate.py) validate only durable structural requirements and avoid overfitting to style or semantic quality
  • Iteration path explicitly stores persistent examples in references/evidence/ and distinguishes working vs. holdout sets
  • Source discovery guidance anticipates thin docs and includes commit-log mining, issue threads, and operational evidence retrieval strategies
Model: claude-haiku-4-5-20251001Analyzed: Jul 11, 2026

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