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Insight critique

Skill allemaar/open-skills/skills/insight-critique

Advisory review workflow. Reviews the last plan, code, architecture, or UI output and returns a structured report: Summary, Strengths, Risks, Fixes. Use when the user runs /critique, asks to "review this", "critique this", or "what's wrong with this", or wants focused feedback on a specific output. Also trigger as a quality gate before /execute. Advisory only — never blocks unless a kernel-prime violation is present. For multi-POV adversarial stress-testing with personas, use /insight-adversarial instead.From its SKILL.md

Install
npx -y skills add allemaar/open-skills --skill insight-critique

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 13 stars13 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

4.2 KB, 747 tokens by cl100k_base, as published. Nobody here has run it

/critique

Advisory review of the last plan, code, architecture, or UI output. Runs four analysis passes and emits a structured report. Never blocks — advisory only.

Structured execution spec: protocol.yon. Read it for the canonical rules and step sequence; this file is explanation. The two must stay in sync — if you edit one, update the other and refresh the @STAMP date.

Caller Options. Before executing, run the Caller Options protocol (caller-options/SKILL.md): triage this invocation for material optionality across the venues and modes declared in front-matter; if one path clearly dominates, proceed silently; otherwise surface the options to the caller. A resolved-invocation marker means COP already ran — execute the fixed combination directly, do not re-enter COP.

Phase 1 — Classify

Identify what is being critiqued. Pick exactly one: Code, Plan, Architecture, UI. If the subject is ambiguous, ask for clarification before proceeding.

Phase 2 — Analysis

Run all four passes. Passes 1–3 are independent. Pass 4 depends on Risks.

  1. Summary — what is this? State purpose, scope, and approach concisely.
  2. Strengths — what is well-designed, sound, or admirable? Be specific. Do not pad.
  3. Risks — what is fragile, dangerous, underspecified, or likely to fail? Rank by severity: High / Medium / Low.
  4. Fixes — for each risk, propose a concrete actionable change. Distinguish must-fix from nice-to-fix.

Phase 3 — Render Report

Output a structured report with four labeled sections: Summary, Strengths, Risks, Fixes. Then set a verdict:

  • ✅ Approved — all risks are Low or cosmetic
  • ⚠️ Conditional — risks present but fixable; apply fixes then proceed to /plan-execute
  • 🚫 Not Approved — High risks present; /plan-create or a redesign is required

Constraints

  • Advisory only. Never block or halt the user's work unless a kernel-prime violation is detected.
  • Never mark Approved when any risk is rated Medium or above.
  • Do not pad Strengths to soften the critique. If there are few strengths, say so.

Downstream

Suggest the natural next command — these mirror the next-skills: front-matter:

  • /insight-adversarial — stress-test the critiqued work from multiple POVs
  • /plan-create — if the verdict is 🚫 Not Approved and a redesign is needed
  • /plan-execute — apply the targeted fixes / proceed if the verdict is ✅ Approved or ⚠️ Conditional

Human output. This skill's handler-facing output obeys the human-output contract (human-output/SKILL.md).

Next skills. On completion, run the Next Skills protocol (next-skills/SKILL.md): surface the next-skills recommendations from front-matter for the caller to pick. Offer only — never auto-invoke.

Self-improvement. On completion, run the Self-Improvement Protocol (self-improve/SKILL.md): if this run surfaced a concrete, blocking-or-recurring weakness in this skill, propose a specific fix for the handler to approve. Conservative — silent otherwise. Never auto-apply.

What ships with it: 1 file

5.7 KB alongside SKILL.md

Gives 1 of the 12 instructions most review quality skills give in 747 tokens

Counted across 1,273 of the 2,403 authors here whose files we hold, read 2026-09-06

  • Ask one question at a timein 63 of 1273, across 62 files
  • Provide a recommended answer for each questionin 47 of 1273, across 45 files
  • Rank findings by severityhere, and in 44 of 1273
  • Use parameterized queries for database accessin 38 of 1273, across 20 files
  • Validate all user input with schemasin 33 of 1273, across 15 files
  • Store secrets in environment variablesin 32 of 1273, across 14 files
  • Explore the codebase to answer questionsin 31 of 1273, across 29 files
  • Store tokens in httpOnly cookiesin 30 of 1273, across 12 files
  • Implement rate limiting on API endpointsin 30 of 1273, across 12 files
  • Sanitize user-provided HTMLin 29 of 1273, across 11 files
  • Return generic error messages to usersin 28 of 1273, across 10 files
  • Cite file and line for every findingin 28 of 1273, across 25 files

Said here and by no other author read

  • Run caller options protocol before executing
  • Run self-improvement protocol upon completion
  • Classify subject as code, plan, architecture, or UI
  • Perform summary, strengths, risks, and fixes analysis passes
  • Propose concrete actionable changes for each risk
  • Output report with summary, strengths, risks, and fixes sections

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.