Borrowing it
Nothing to install: this file belongs to Nam-Cheol/namba-ai. 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/Nam-Cheol/namba-ai/main/.agents/skills/namba-plan-pm-review/SKILL.mdgit clone --depth 1 https://github.com/Nam-Cheol/namba-aiWrote 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/nam-cheol/namba-ai/namba-plan-pm-review)<a href="https://agentmods.dev/skills/nam-cheol/namba-ai/namba-plan-pm-review"><img src="https://agentmods.dev/badge/skills/nam-cheol/namba-ai/namba-plan-pm-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/nam-cheol/namba-ai/namba-plan-pm-review"><img src="https://agentmods.dev/badge/skills/nam-cheol/namba-ai/namba-plan-pm-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00021 | $0.00504 |
| Opus 5.5 | $0.00008 | $0.00202 |
| Sonnet 5.5 | $0.00004 | $0.00101 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
namba-plan-pm-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 2mo 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.
What it actually says
State effect: mutating review update. Writes SPEC review artifacts and readiness summaries.
Generated instruction contract for this command skill:
- Purpose: keep the role or command scope explicit, bounded, and testable.
- Boundary: honor read-only versus mutating state effects, configured sandbox mode, and assigned file or workflow ownership.
- Required output: report concrete actions, changed paths or artifacts, validation evidence, and pass/fail status or blockers.
- Pass/fail criteria: claim success only when acceptance criteria and configured validation are satisfied; otherwise name the exact blocker and impact.
- Evidence expectations: cite source artifacts such as SPEC files,
.namba/configs, diffs, test output, PR/check links, or generated manifests instead of relying on unsupported assertions. - Security responsibilities: never expose or commit secrets; treat auth, privacy, destructive commands, permission changes, and external network or credential use as security-sensitive.
- Destructive command and escalation policy: do not run destructive commands unless explicitly requested; request approval for privileged, networked, or sandbox-blocked actions only when the active approval mode allows it, and otherwise report the blocker or use a safe non-escalating path.
- Fallback implementer boundary: if a specialist path is unavailable and the main/default implementer takes over, stay within the assigned scope and preserve the same evidence and validation duties.
- Portability: keep durable guidance non-project-specific unless the current repository config or SPEC explicitly provides the project detail.
Use this skill when the user explicitly says $namba-plan-pm-review or asks for a product review on a SPEC package.
Behavior:
- Resolve the target SPEC from an explicit
SPEC-XXX; otherwise use the latest SPEC under.namba/specs/. - Read
.namba/specs/<SPEC>/spec.md,plan.md, andacceptance.mdbefore writing review notes. - Update
.namba/specs/<SPEC>/reviews/product.mdwith status, reviewer, findings, decisions, follow-ups, and recommendation. - Prefer
namba-product-manageras the review role when subagent routing is appropriate. - Refresh
.namba/specs/<SPEC>/reviews/readiness.mdso the advisory summary reflects the latest review state. - Keep the review advisory by default; surface missing depth or blockers clearly without silently turning the workflow into a hard gate.
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.
- 2mo ago First seen · 28 lines · 21 tokens per session scan A 8f7b51fbf447
namba-plan-pm-review is a skill published in the GitHub repository Nam-Cheol/namba-ai (11 stars, last pushed 12d ago), licensed MIT. It adds 21 tokens to every session and 504 once invoked, about $0.0001 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.
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