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 agentmods add agents/ww-w-ai/bkit-claude-code/pm-lead-skill-patchgit clone --depth 1 https://github.com/ww-w-ai/bkit-claude-codeWrote 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/agents/ww-w-ai/bkit-claude-code/pm-lead-skill-patch)<a href="https://agentmods.dev/agents/ww-w-ai/bkit-claude-code/pm-lead-skill-patch"><img src="https://agentmods.dev/badge/agents/ww-w-ai/bkit-claude-code/pm-lead-skill-patch.svg" alt="Measured on agentmods" 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 | $0.00055 | $0.00688 |
| Opus 5 | $0.00028 | $0.00344 |
| Sonnet 5 | $0.00011 | $0.00138 |
| Haiku 4.5 | $0.00006 | $0.00069 |
Grade A, and why
pm-lead-skill-patch 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 4d 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
pm-lead Skill Needs Extension (Patch)
Purpose
기존 pm-lead 에이전트의 Phase 4 (PRD Synthesis) 완료 후, skill-needs-extractor 에이전트를 자동 호출하여 PRD에서 스킬 니즈를 추출한다.
IMPORTANT: 이 패치는 기존 bkit 플러그인 파일을 수정하지 않는다. project-local 에이전트로서 pm-lead 워크플로우에 후처리를 추가한다.
When to Activate
이 패치가 적용되는 조건:
/pdca pm {feature}완료 후 PRD 파일이 생성되었을 때docs/00-pm/{feature}.prd.md파일이 존재할 때- 사용자가 PRD 생성 결과를 확인한 후
Extension Flow
After pm-lead Phase 4 completes:
-
Detect PRD completion:
- Check if
docs/00-pm/{feature}.prd.mdwas just created/updated - Verify it has the expected PRD structure (## Part 5: Product Requirements)
- Check if
-
Invoke skill-needs-extractor:
- Pass the feature name
- Pass the PRD path
-
Present results to user:
PRD 생성 완료: docs/00-pm/{feature}.prd.md Skill Needs Analysis: - N개 스킬 니즈 식별 - N개 기존 스킬로 커버 가능 - N개 신규 스킬 필요 신규 스킬을 생성하시겠습니까? (Y/N) - Y: 각 GAP 스킬에 대해 /skill-create 실행 - N: 나중에 /skill-create 으로 수동 생성 -
If user confirms:
- For each GAP skill need, prepare skill-create input
- Guide user through
/skill-create {name}for each
Integration Points
[pm-lead] Phase 1-4
|
v
[PRD created] docs/00-pm/{feature}.prd.md
|
v
[pm-lead-skill-patch] (this agent)
|
v
[skill-needs-extractor] agent
|
v
[.bkit/skill-needs.json] output
|
v
[User prompt] "Create N new skills?"
|
v
[skill-create] skill (for each GAP item)
Notes
- This agent does NOT modify the core pm-lead agent
- It operates as a post-processing step
- Can be skipped if user runs
/pdca plandirectly without/pdca pm - Skill needs extraction is additive -- never removes existing skills
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.
- 4d ago First seen · 95 lines · 55 tokens per session scan A ed1fe280160c
pm-lead-skill-patch is an agent published in the GitHub repository ww-w-ai/bkit-claude-code (595 stars, last pushed 18d ago), licensed Apache-2.0. It adds 55 tokens to every session and 688 once invoked, about $0.0003 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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