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-run/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-run)<a href="https://agentmods.dev/skills/nam-cheol/namba-ai/namba-run"><img src="https://agentmods.dev/badge/skills/nam-cheol/namba-ai/namba-run/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-run"><img src="https://agentmods.dev/badge/skills/nam-cheol/namba-ai/namba-run.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 | $0.00019 | $0.01147 |
| Opus 5.5 | $0.00008 | $0.00459 |
| Sonnet 5.5 | $0.00004 | $0.00229 |
| Haiku 4.5 | $0.00002 | $0.00115 |
Grade A, and why
namba-run 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 — 38 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-run, namba run SPEC-XXX, or asks to execute a SPEC through Namba.
Behavior:
- Read
.namba/specs/<SPEC>/spec.md,plan.md, andacceptance.mdbefore implementation. - Read
.namba/specs/<SPEC>/reviews/readiness.mdwhen it exists so advisory review depth is visible before coding starts. - Read
.namba/specs/<SPEC>/frontend-brief.mdwhen it exists; it is the canonical source for frontend task classification and gate state. - In an interactive Codex session, prefer Codex-native in-session execution over recursively calling
namba run. - Only use the standalone CLI runner for
--solo,--team,--parallel,--dry-run, or when the user explicitly wants the non-interactive runner path. - For
--solo, stay inside one runner unless one domain clearly dominates and a single specialist would materially reduce risk. - For
--team, prefer one specialist when one domain dominates, expand to two or three only when acceptance spans multiple domains, and keep one integrator plus final validation owner in the workspace. - For
--team, honor each selected role'smodelandmodel_reasoning_effortmetadata from.codex/agents/*.tomlso planner/reviewer/security roles can think harder without making every delivery role heavy. - Route art direction, palette/tone logic, composition, motion intent, Figma critique, and generic-section redesign work to
namba-designer; route component boundaries, state ownership, and UI delivery planning tonamba-frontend-architect; route approved UI implementation tonamba-frontend-implementer; route mobile-specific UI delivery tonamba-mobile-engineer; route API, schema, and pipeline work to backend/data; route auth, secrets, and compliance work to security; route deployment and runtime work to devops. frontend-majorwork must not move into architecture or implementation untilfrontend-brief.mdshows coherent problem, reference, critique, decision, prototype evidence, a complete Do-Not Design Contract with reference-driven asset manifest, generated-image decision fields, generation plan, and aligned design clearance;frontend-minorkeeps the lightweight advisory path.- Treat review readiness as advisory by default for non-frontend and
frontend-minorwork, but block explicitfrontend-majorexecution when the frontend brief is missing required evidence, internally contradictory, mismatched with design-review summaries, or missing/insufficient negative-first contract evidence. - For
frontend-major, first frontend and first major screen phases default toAsset mode: generated-imagesandImagegen requirement: required; acceptexisting-assetsornot-applicableonly with validator-readable Asset decision proof. - For
frontend-majorimplementation results, require aDo-Not Design Violation Checkthat cites changed files, names any banned pattern found, and cites the exception path when one is used; whenImagegen requirement: requiredis present, requireGenerated Asset Evidencewith manifest path and repeatable Asset ID blocks containing generated file, saved asset path, prompt summary, intended UI usage, and rendered usage evidence. - For browser-rendered frontend work, use managed server lifecycle, wait for rendered DOM state, capture screenshots, inspect console errors, and prefer Playwright checks when the surface runs in a browser.
- Run validation commands from
.namba/config/sections/quality.yamland finish withnamba sync. Usenamba prandnamba landfor the GitHub handoff and merge cycle instead of overloadingsync. - Collaboration defaults: branch from
main, open the PR intomain, write the PR in Korean, and request Codex review only whennamba pr --reviewor queue--reviewis explicit; use@codex reviewas the request command.
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 · 38 lines · 19 tokens per session scan A 92f75192d9e3
namba-run is a skill published in the GitHub repository Nam-Cheol/namba-ai (11 stars, last pushed 12d ago), licensed MIT. It adds 19 tokens to every session and 1,147 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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