Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Jamie-BitFlight/claude_skills --skill forensic-reviewgit clone --depth 1 https://github.com/Jamie-BitFlight/claude_skillsWrote 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/jamie-bitflight/claude_skills/forensic-review)<a href="https://agentmods.dev/skills/jamie-bitflight/claude_skills/forensic-review"><img src="https://agentmods.dev/badge/skills/jamie-bitflight/claude_skills/forensic-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/jamie-bitflight/claude_skills/forensic-review"><img src="https://agentmods.dev/badge/skills/jamie-bitflight/claude_skills/forensic-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00048 | $0.01920 |
| Opus 5 | $0.00024 | $0.00960 |
| Sonnet 5 | $0.00010 | $0.00384 |
| Haiku 4.5 | $0.00005 | $0.00192 |
Grade A, and why
forensic-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 7d 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 — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SAM Stage 6 — Forensic Review
Role
SAM Stage 6 delegates the concrete review work to @dh:code-reviewer. This skill is the
orchestration wrapper: it resolves the task context, dispatches the agent, and maps its
structured output back to the SAM pipeline verdict.
Producer and reviewer must always be different agents — never invoke this skill from the same agent that executed the task.
Core Principle
AI cannot reliably self-evaluate. The agent that wrote the code cannot objectively assess its own work. Forensic review uses a separate agent with fresh context to verify claims against observable evidence.
When to Use
- After Stage 5 Execution produces ARTIFACT:EXECUTION
- For each completed task before marking it as done
- When re-reviewing after a NEEDS_WORK remediation cycle
Process
flowchart TD
Start([ARTIFACT:EXECUTION + ARTIFACT:PLAN]) --> R1[1. Resolve task context]
R1 --> R2[2. Dispatch @dh:code-reviewer]
R2 --> R3[3. Consume verdict from STATUS output]
R3 --> R4[4. Read code-review artifact]
R4 --> Decide{Verdict?}
Decide -->|PASS| Complete[Verdict — COMPLETE]
Decide -->|NEEDS-WORK or FAIL| NeedsWork[Verdict — NEEDS_WORK]
Complete --> Done([ARTIFACT:REVIEW registered by agent])
NeedsWork --> Remediate[Create remediation tasks from blocking findings]
Remediate --> Done
Step 1 — Resolve Task Context
Read the task via MCP:
sam_task(plan="{plan_id}", task="{task_id}", config={"action": "read"})
{plan_id} and {task_id} are the address already supplied to the call above — retain them as-is
for the rest of this workflow; sam_task(action="read") returns a TaskAssignment with no
top-level plan_id/task_id fields (the plan is plan-number, the task is nested at task.id),
so do not attempt to re-extract the address from the response. Never parse plan_id for a plan
number or slug — read those from sam_plan(config={"action": "read"}).
From the response, extract:
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.
- 7d ago First seen · 195 lines · 48 tokens per session scan A d0a9a52ae604
forensic-review is a skill published in the GitHub repository Jamie-BitFlight/claude_skills (66 stars, last pushed today), licensed MIT. It adds 48 tokens to every session and 1,920 once invoked, about $0.0002 per session on Opus 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 2026-09-03.
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