Skip to content
cccskills
FreePublished on GitHub

structured-output

Formats review deliverables with consistent structure for comparable findings. Use when finalizing any review or analysis that must be shared or compared.

The English summary is being prepared. Showing the original description.

See how to install

Files included (1)

  • SKILL.md4.7 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Structured Output

When To Use

  • When finalizing any review or analysis.
  • To format findings in a consistent way that names specific next steps.
  • Before presenting results to stakeholders or committing them to documentation.

When NOT To Use

  • Capturing evidence during analysis - use proof-of-work
  • Reviewing changes - use diff-analysis or review-core first

Activation Patterns

Trigger Keywords: format, structure, deliverable, report, organize, present, consistent Contextual Cues:

  • "format this as a report" or "structure the output"
  • "create a deliverable" or "present these findings"
  • "organize this consistently" or "standardize the format"
  • "make this actionable" or "prepare for stakeholders"

Auto-Load When: Finalizing any analysis deliverable or when consistent formatting is requested.

Required TodoWrite Items

  1. structured-output:template-selected
  2. structured-output:findings-formatted
  3. structured-output:actions-assigned
  4. structured-output:appendix-attached

Mark each item complete as you finish the corresponding step.

Step 1: Select Template (structured-output:template-selected)

  • Choose output format based on deliverable type:
    • Review Report: Summary, Findings, Recommendations, Evidence.
    • PR Description: Summary, Changes, Test Plan, Notes.
    • Release Notes: Highlights, Breaking Changes, Fixes, Credits.
    • Incident Report: Timeline, Impact, Root Cause, Remediation.
  • Confirm audience and required detail level.

Step 2: Format Findings (structured-output:findings-formatted)

  • Use consistent finding structure:
    ### [SEVERITY] Finding Title
    **Location**: file.rs:123
    **Anchor**: `verbatim source text copied from line 123`
    **Category**: Security | Performance | Correctness | Style
    **Description**: Brief explanation of the issue.
    **Evidence**: [E1, E2] - Reference to evidence log.
    **Recommendation**: Specific remediation steps.
    
    Verification: Run the command with --help flag to verify availability.
  • Severity levels: CRITICAL, HIGH, MEDIUM, LOW, INFO.
  • Order findings by severity, then by file location.
  • Anchor is mandatory and grounds the finding. Copy the exact source text at Location (not a paraphrase). It is what a second pass re-reads to confirm the finding is real. A finding whose anchor does not appear at its cited line is treated as a hallucination and dropped. The check is mechanical: imbue:review-core Step 5 runs plugins/imbue/scripts/citation_verifier.py over the findings.

Step 3: Assign Actions (structured-output:actions-assigned)

  • Convert findings to action items with assignee and priority:
    ## Action Items
    - [ ] [HIGH] Fix SQL injection in auth.py:45 (@security-team, P1)
    - [ ] [MEDIUM] Add input validation to API endpoint (@backend, P2)
    - [ ] [LOW] Update deprecated dependency (@devops, P3)
    
    Verification: Run the command with --help flag to verify availability.
  • Include owner assignment where known.
  • Add priority indicators (P1/P2/P3) for triage.
  • Note dependencies between actions.

Step 4: Attach Appendix (structured-output:appendix-attached)

  • Compile supporting materials:
    ## Appendix
    ### A. Commands Run
    [Full evidence log from imbue:proof-of-work]
    
    ### B. External References
    [Citations and documentation links]
    
    ### C. Raw Data
    [Large outputs, full diffs, or data exports]
    
    Verification: Run the command with --help flag to verify availability.
  • Keep main report concise; details in appendix.
  • validate appendix is navigable with clear section headers.

Output Quality Checklist

Before finalizing:

  • Every finding carries a verbatim Anchor the citation verifier resolved (no unverified findings ship).
  • All findings have evidence references.
  • Severity levels are justified.
  • Recommendations are specific and name the next step.
  • No orphaned sections or placeholder text.
  • Format renders correctly in target medium (GitHub, Confluence, etc.).

Exit Criteria

  • Todos completed with formatted deliverable.
  • Output follows selected template structure.
  • Stakeholders can act on findings without clarification.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.

The English summary is being prepared. Showing the original description.

athola/claude-night-market343Updated Oct 17, 2026

Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.

The English summary is being prepared. Showing the original description.

athola/claude-night-market343Updated Oct 17, 2026

Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.

The English summary is being prepared. Showing the original description.

athola/claude-night-market343Updated Oct 17, 2026

Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.

The English summary is being prepared. Showing the original description.

athola/claude-night-market343Updated Oct 17, 2026

Evaluates API surface design, consistency, and exemplar alignment. Use when reviewing public API changes or before releasing a new API surface.

The English summary is being prepared. Showing the original description.

athola/claude-night-market343Updated Oct 17, 2026

Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.

The English summary is being prepared. Showing the original description.

athola/claude-night-market343Updated Oct 17, 2026

See all skills by athola

Report a problem with this skill