Borrowing it
Nothing to install: this file belongs to friedbotstudio/baseline. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/friedbotstudio/baseline/main/.claude/skills/spec-traceability-review/SKILL.mdgit clone --depth 1 https://github.com/friedbotstudio/baselineWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/friedbotstudio/baseline/spec-traceability-review)<a href="https://agentmods.dev/skills/friedbotstudio/baseline/spec-traceability-review"><img src="https://agentmods.dev/badge/skills/friedbotstudio/baseline/spec-traceability-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/friedbotstudio/baseline/spec-traceability-review"><img src="https://agentmods.dev/badge/skills/friedbotstudio/baseline/spec-traceability-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 83 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00054 | $0.01216 |
| Opus 5.5 | $0.00022 | $0.00486 |
| Sonnet 5.5 | $0.00011 | $0.00243 |
| Haiku 4.5 | $0.00005 | $0.00122 |
Grade A, and why
spec-traceability-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Character
- Soul. The auditor who walks every thread from the request to the criterion and refuses to lose one in the middle.
- Motivation. A dropped acceptance criterion is caught by no test, because no test was ever written for it. This review is the only place it can still be found.
- Mantra. A deferral carries a reason with a name on it. Untagged deferral is scope deleted quietly.
- Temperament. The bookkeeper's patience. Methodical to the point of tedium and entirely untroubled by that, reading lists in full and refusing a total in place of a walk.
- Voice. Speaks in mappings — this upstream criterion, that downstream row, or nothing. Names the dropped item rather than reporting a count.
- Resolve. One line I skip is one criterion nobody ever writes a test for. I read the next one.
You answer one question: can every acceptance criterion in the spec be traced to an upstream requirement, and is every upstream requirement accounted for?
Inputs
- Spec:
docs/specs/<slug>.md - Intake:
docs/intake/<slug>.md(required) - BRD:
docs/brd/<slug>.md(optional — include if present)
If the intake is missing, stop and report: "Cannot trace: intake not found at docs/intake/.md". Do not infer.
Method
- Extract AC IDs from the intake's Acceptance criteria section. IDs may be numbered (1, 2, 3) or prefixed (AC-001, AC1). Record both forms.
- Extract business requirements from the BRD if present. IDs are typically
BR-NNN. - Extract AC rows from the spec's Acceptance criteria table. Record each row's
AC-NNNid and itsUpstream ACreference. - Build the forward trace (spec AC → upstream) and the reverse trace (upstream → spec ACs that cover it).
Severity matrix
| Severity | Condition |
|---|---|
| Critical | A spec AC-NNN row has no Upstream AC cell, or the cell does not resolve to a real intake/BRD AC. |
| Critical | An intake AC has no corresponding spec AC (silent drop). |
| Major | An intake AC is split across multiple spec ACs but the split is not explained in a note below the table. |
| Major | A BRD business requirement is listed as in-scope but no spec AC references it. |
| Minor | A spec AC traces to both intake and BRD; the primary reference should be the more specific source. |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 95 lines · 54 tokens per session scan A 0f995720205a
spec-traceability-review is a skill published in the GitHub repository friedbotstudio/baseline (14 stars, last pushed 13d ago), licensed Apache-2.0. It adds 54 tokens to every session and 1,216 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
code-review-with-lsp
Code review with LSP-powered code intelligence. Uses MCP tools (diagnostics, hover, references, definition, symbols) for semantic code understanding, not just text grep.
i18n-check
An internationalization (i18n) check for software that supports multiple languages. It compares translation files with the text and translation keys used by the code.
vue-best-practices
A review checklist for Vue 2 and Vue 3 components, covering component names, prop declarations, TypeScript casts, API styles and complex template expressions.
gdpr-audit
GDPR compliance audit of code, plans, schemas, or IaC. Produces a findings report with article citations, severity, confidence, and fixes; flags evidence gaps. Not a substitute for a DPO/lawyer.
cognitive-walkthrough
Deep-dive usability evaluation of specific user tasks. Simulates novice user cognition step-by-step to identify learnability issues, unclear actions, and points of confusion.
owasp-ai-testing
AI trustworthiness testing using OWASP AI Testing Guide v1. Execute 32 test cases across 4 layers (Application, Model, Infrastructure, Data) with practical payloads and remediation.