namba-ai: Skill for Claude Code

.agents/skills/namba-plan-review/SKILL.md

namba-plan-review is a skill for Claude Code, Codex from Nam-Cheol/namba-ai. It costs 24 tokens per session (980 once invoked), scanned A, original, MIT.

A command for creating a project specification, reviewing implementation plans in parallel, and checking whether the project is ready for the next step. It follows explicit rules for scope, evidence, security, and validation.

In plain words
What is it for?
Use it to prepare a SPEC, obtain several plan reviews, validate readiness, and document the resulting changes, tests, artifacts, or blockers.
Why use it?
It helps turn an unclear change into a checked plan and makes the result easier to verify. It also requires reporting changed files, evidence, pass or fail status, and blockers.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; installed under .agents/ (shared by several agents); $skill-name invocation.

This is Nam-Cheol/namba-ai's own configuration. It tells Claude Code and Codex how to work on namba-ai itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything namba-ai configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/Nam-Cheol/namba-ai/main/.agents/skills/namba-plan-review/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Nam-Cheol/namba-ai

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for namba-plan-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/nam-cheol/namba-ai/namba-plan-review/github.svg)](https://agentmods.dev/skills/nam-cheol/namba-ai/namba-plan-review)
Your own site
<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.

agentmods 80×15 button for namba-plan-review

Your own site · 80×15
<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>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 980 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00024 $0.00980
Opus 5 $0.00012 $0.00490
Sonnet 5 $0.00005 $0.00196
Haiku 4.5 $0.00002 $0.00098

Measured 12d ago against content hash aab17b30c143, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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 12d 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.

.agents/skills/namba-plan-review/SKILL.md · 35 lines

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 with namba plan for feature work, namba harness for reusable agent/skill/workflow/orchestration work, or namba fix --command plan for 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 namba CLI 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 dedicated spec/... branch in the current workspace by default, treat --current-workspace as the explicit current-branch escape hatch, and do not create planning worktrees.
  • Read .namba/specs/<SPEC>/spec.md, plan.md, and acceptance.md before 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-review as the three authoritative review tracks.
  • Prefer namba-product-manager, namba-planner, and namba-designer for the three review tracks, and use namba-plan-reviewer as 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/*.md to 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.md after each review and validation cycle so the advisory summary stays current.
  • Before ending, inspect .namba/specs/<SPEC>/reviews/readiness.md; if it does not say Cleared 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-XXX or 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.

Read the full file on GitHub · 35 lines

Changes

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.

  1. 12d ago First seen · 35 lines · 24 tokens per session scan A aab17b30c143

Subscribe to this mod's changes

namba-plan-review is a skill published in the GitHub repository Nam-Cheol/namba-ai (11 stars, last pushed 19d ago), licensed MIT. It adds 24 tokens to every session and 980 once invoked, about $0.0001 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 2026-08-30.

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