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 skills add nguyenvanphituoc/shapeup-sdlc-plugin --skill coachgit clone --depth 1 https://github.com/nguyenvanphituoc/shapeup-sdlc-pluginWrote 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/nguyenvanphituoc/shapeup-sdlc-plugin/coach)<a href="https://agentmods.dev/skills/nguyenvanphituoc/shapeup-sdlc-plugin/coach"><img src="https://agentmods.dev/badge/skills/nguyenvanphituoc/shapeup-sdlc-plugin/coach.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 5.1 | $0.00130 | $0.03115 |
| Opus 5 | $0.00065 | $0.01558 |
| Sonnet 5 | $0.00026 | $0.00623 |
| Haiku 4.5 | $0.00013 | $0.00312 |
Grade A, and why
coach 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 8d 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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Coach Skill — RLHF for the harness
The /coach skill closes the learning loop. After a feature ships, the PO/TL drops raw,
unstructured feedback at the L4 Gate ("the executor keeps over-engineering DTOs", "the BA
under-scopes mobile"). The coach distills that into durable guidelines and files them where
the relevant worker will read them on its next run — so the lesson is learned once and applied
by the whole team forever, not re-explained every sprint.
Two properties make this useful and were missing before:
- Team-shared, not local. Guidelines are written under
shapeup/knowledge-base/, which is committed (the.shapeup/run-trace root is gitignored — guidelines written there would never reach a teammate). Agit pullis all a team member needs to inherit the harness's accumulated judgment. - Read back, not write-only. Each guideline is filed under the one skill that will act on
it, in that skill's own file, so the consumer loads only its own rules.
task-executor,ba-pitch-analyzer, andqa-edge-huntereach read their file at the top of their run.
PO feedback at L4 ─► /coach ─► [parse into candidate rules] ─► ⏸ GATE COACH-1 (categorize, ask — never assume)
│
shapeup/knowledge-base/<skill>.md ◄───┤ (one file per coachable skill, committed)
│
next run: task-executor / ba-pitch-analyzer / qa-edge-hunter reads its own file
│
shapeup/knowledge-base/harness-defects.md ◄───────┘ (mechanism at fault →
drafted raw idea for the Betting Table — read by no worker, committed)
Coachable skills (the only valid categories)
A guideline is only useful if a worker reads it back. These three workers have a read-side hook; they are the complete set of categories the gate may offer:
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.
- 8d ago First seen · 203 lines · 130 tokens per session scan A 60f3e5608db8
coach is a skill published in the GitHub repository nguyenvanphituoc/shapeup-sdlc-plugin (2 stars, last pushed today), licensed MIT. It adds 130 tokens to every session and 3,115 once invoked, about $0.0006 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 2026-08-31.
Other skills, from other repositories
agent-swarm-issue
Agent skill for swarm-issue - invoke with $agent-swarm-issue.
agent-swarm
Agent skill for swarm - invoke with $agent-swarm.
moai-workflow-worktree
Git worktree management for parallel SPEC development with isolated workspaces, automatic branch registration, and seamless MoAI-ADK integration. Use when setting up parallel development environments.
babysit-babysitter-issues
This skill should be used when the user asks to "babysit issues", "work on assigned issues", "check a5c-agent issues", "process babysitter issues", or wants to find and work on open GitHub issues assigned to a5c-agent in the babysitter repo.
cog-meeting-processing
Process meeting recordings and transcripts into decisions, action items, and team dynamics.
cog-team-intelligence
Cross-reference GitHub, Linear, Slack, and PostHog with bidirectional sync for team briefs.