skill-review — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited skill-review (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Core responsibility: Find real behavioral gaps in a Lattice skill by reviewing it through three independent personas. Each persona sees the skill with different eyes, cares about different things, and may surface different gaps. The combined findings should be more practical and complete than any single review.
Input: One skill path or skill name.
Output: A unified findings report — only the high-confidence, practical gaps from all three personas, merged, deduplicated, pruned, and ordered by severity — with proposed fixes.
Review standard: Prefer omission over speculation. Only report findings you are highly confident would surface in normal use, belong to this skill's responsibility, and would materially improve outcomes if fixed. A valid review may conclude that no material practical gaps remain.
How to verify this skill did its job:
Read the full SKILL.md and all referenced files (defaults.md, template.md, references/).
Form a clear understanding of:
If the skill is composed by molecules, consumes refiner output, or depends on other skills, read the relevant upstream/downstream files too. Review against actual runtime usage, not an imagined standalone use case.
Based on what the skill does and who it serves, propose 3 personas whose perspectives would surface the most useful gaps.
Persona selection logic:
| If the skill... | Consider personas like... |
|---|---|
| Is a molecule used by product/BA people | Senior PM, Business Analyst, Lead Developer consuming the output |
| Is an atom enforcing code quality | Code reviewer, Junior developer following the rules, Architect checking for structural gaps |
| Is a refiner configuring standards | Team lead setting standards, New team member onboarding, AI assistant consuming the standards doc |
| Is a dev-tool skill (forge, validator, sync) | Lattice maintainer, First-time skill creator, Experienced developer new to Lattice |
| Spans product + technical audiences | One product persona, one practitioner persona, one technical persona |
Present 3 proposed personas with a one-line rationale for each:
"For [skill-name], I'd review from these three perspectives: 1. [Persona A] — because [why this skill matters to them / what they'd be looking for] 2. [Persona B] — because [different angle this persona brings] 3. [Persona C] — because [third angle, ideally the consumer of the skill's output]
Want to use these, swap any out, or add your own?"
Wait for the user to confirm or adjust before proceeding.
Do NOT proceed to Step 3 until personas are agreed.
For each persona in sequence, fully inhabit that perspective. Forget the other personas while you are in one.
3a — Scenario generation
Generate the smallest realistic set of scenarios needed to stress this skill (typically 4–6; do not force all scenario types). Consider:
Use only the scenarios that genuinely apply to this skill. Skip any case that does not fit. Better 4 relevant scenarios with real findings than 8 forced scenarios with speculative ones.
For each chosen scenario, follow the skill's instructions literally. Treat silence as a gap only if ALL are true:
If any of these are false, do not record a finding.
3b — Persona-specific concerns
Use these as attention prompts, not finding quotas. They help you notice classes of problems; they do not guarantee that a real finding exists.
Each persona has things they care about that others might miss:
3c — Record findings for this persona
Before recording any finding, run this filter:
If any answer is "no", drop the finding. Mere possibility is not enough.
Format each finding:
[Persona: {name}]
Scenario: {which realistic scenario surfaced this}
Evidence: {exact line/section/instruction that supports the gap}
Type: CRITICAL | WARNING | OBSERVATION
Gap: {what the skill is silent about or handles incorrectly — specific}
Fix: {specific addition or change to the SKILL.md — exact enough to write}
Confidence: {90%+ and why}After all three personas have completed their analysis:
(Found by: Persona A, Persona C)Severity definitions:
Do not force every severity bucket to be non-empty. It is valid to report zero observations, zero warnings, or no findings at all.
## Skill Review — {skill-name}
Personas: {Persona A} | {Persona B} | {Persona C}
If no retained findings remain after pruning:
No material practical gaps found. The skill appears ready for use as written.
Otherwise present:
### Critical Gaps (must fix before using this skill)
GAP-1: {gap title}
Found by: {Persona A, Persona C}
Scenario: {which scenario surfaced it}
Evidence: {exact line/section/instruction}
Problem: {what the skill is silent about or handles incorrectly}
Fix: {specific change}
Confidence: {90%+ and why}
GAP-2: ...
### Warnings (should fix — will cause confusion or inconsistency)
WARN-1: ...
### Observations (consider — not blocking)
OBS-1: ...
---
Summary: {N} critical, {M} warnings, {P} observations
Highest-confidence findings (after pruning and corroboration): GAP-1, WARN-2
Recommended fix order: [ordered list]If findings remain, ask: "Which findings should I fix? Recommend starting with the critical gaps — especially those that are both practical and corroborated."
If no findings remain, state that no fixes are recommended and stop.
For each confirmed fix:
After all fixes: present a brief closure summary — gaps closed, gaps deferred, what a second run of this skill would likely find.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.