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-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-review)<a href="https://agentmods.dev/skills/nam-cheol/namba-ai/namba-plan-review"><img src="https://agentmods.dev/badge/skills/nam-cheol/namba-ai/namba-plan-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-review"><img src="https://agentmods.dev/badge/skills/nam-cheol/namba-ai/namba-plan-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 | $0.00024 | $0.00980 |
| Opus 5.5 | $0.00010 | $0.00392 |
| Sonnet 5.5 | $0.00005 | $0.00196 |
| Haiku 4.5 | $0.00002 | $0.00098 |
Grade A, and why
namba-plan-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.
How it starts
The opening of the file, as written. The whole thing — 35 lines — stays where its author put it; the contents beside it link to each section on GitHub.
State effect: mutating workflow entry point. Use help/probe paths read-only, and otherwise expect repository state or GitHub state to change.
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-review, asks to create a SPEC and run the full pre-implementation review loop, or wants namba plan plus the review flow bundled into one skill.
Behavior:
- Resolve the target SPEC from an explicit
SPEC-XXX; otherwise create the next SPEC withnamba planfor feature work,namba harnessfor reusable agent/skill/workflow/orchestration work, ornamba fix --command planfor bugfix planning. - When creating a new SPEC from a user request, inherit the same clarification gate as
$namba-plan: ask first and do not run the CLI while the raw request is still vague, short, or missing Goal/Scope/Constraints/Acceptance. - Prefer the installed
nambaCLI for the SPEC-creation step when it is available; keep.namba/as the source of truth if you need to do the setup manually. - Inherit the same safe-by-default planning branch contract as
namba plan: create or switch to the dedicatedspec/...branch in the current workspace by default, treat--current-workspaceas the explicit current-branch escape hatch, and do not create planning worktrees. - Read
.namba/specs/<SPEC>/spec.md,plan.md, andacceptance.mdbefore launching reviews or revising the planning artifacts. - Launch product, engineering, and design review passes in parallel when subagent routing is available, using
$namba-plan-pm-review,$namba-plan-eng-review, and$namba-plan-design-reviewas the three authoritative review tracks. - Prefer
namba-product-manager,namba-planner, andnamba-designerfor the three review tracks, and usenamba-plan-revieweras the aggregate validator when custom-agent routing is available. - After the three review tracks finish, run an aggregate validation pass over
spec.md,plan.md,acceptance.md, and.namba/specs/<SPEC>/reviews/*.mdto check coverage gaps, contradictions, and whether the advisory readiness state is credible. - If the aggregate validator finds issues, revise the SPEC or review artifacts directly, rerun only the affected review tracks, and repeat the validation loop instead of restarting every pass blindly.
- Refresh
.namba/specs/<SPEC>/reviews/readiness.mdafter each review and validation cycle so the advisory summary stays current. - Before ending, inspect
.namba/specs/<SPEC>/reviews/readiness.md; if it does not sayCleared reviews: 3/3, do not report the review loop as complete. Continue the review loop when useful, or make the final next-work item explicitly name$namba-plan-review SPEC-XXXor the missing individual review skills to run next. - Keep the loop bounded and explicit: stop when the readiness state is clear enough to proceed or when the remaining blockers are concrete enough that another loop would be redundant.
- Keep the whole flow advisory by default; missing depth or blockers should be visible, not silently converted 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 · 35 lines · 24 tokens per session scan A aab17b30c143
namba-plan-review is a skill published in the GitHub repository Nam-Cheol/namba-ai (11 stars, last pushed 12d ago), licensed MIT. It adds 24 tokens to every session and 980 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.
Other skills, from other repositories
autofix-pr
Watch a pull request and fix it from a worktree of its own - CI failures, review feedback from trusted authors and merge conflicts are fixed, pushed to the PR branch and answered on the PR under the user's git and gh identity. Usage - /autofix-pr [ | ] [--once] [--every ] [--no-reply] [--yes] [instructions]…
simplify
Review recent code changes for reuse, code quality, and efficiency, then directly apply straightforward cleanup improvements. Use when the user wants a post-implementation cleanup pass, pre-PR polish, or asks to simplify/refine recent changes. Invoke with /simplify or /simplify .
review-team
Use when assigned a review or when an authored review boundary is reached.
autofix
Review and repair current local changes until they converge, or run Qwen Code Autofix issue and review workflows from GitHub Actions.
find-simplifications
Use for a periodic repo-wide sweep of qwen-code for accumulated excess surface — dead components and files, orphaned locale keys, exports nothing consumes, added-then-removed scaffolding — filing candidates on a tracking issue and landing only what a maintainer has said yes to. Repo-wide and evidence-first; every…
swarm-pr-review
Run a graph-guided, tool-augmented PR review using context packing, parallel exploration, mandatory repository-agnostic risk-family coverage with dispatch scaled to diff size and risk, independent reviewer validation, critic challenge, and metrics writeback. Use for deep pull request review with low false-positive…