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 commands/nguyenvanphituoc/shapeup-sdlc-plugin/shapegit 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/commands/nguyenvanphituoc/shapeup-sdlc-plugin/shape)<a href="https://agentmods.dev/commands/nguyenvanphituoc/shapeup-sdlc-plugin/shape"><img src="https://agentmods.dev/badge/commands/nguyenvanphituoc/shapeup-sdlc-plugin/shape.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 | $0.00018 | $0.00161 |
| Opus 5 | $0.00009 | $0.00081 |
| Sonnet 5 | $0.00004 | $0.00032 |
| Haiku 4.5 | $0.00002 | $0.00016 |
Grade A, and why
shape 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 3d 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
Use the shapeup skill on $ARGUMENTS.
This is Phase 1 of the pipeline — it runs before any code and produces the shaping.md and breadboard.md files (the pitch) that the
Betting Table decides on. Default to the full sequence (full); when the user names a single
step, pass it through as the sub-command: shaping, breadboarding, spike, framing-doc,
kickoff-doc, or breadboard-reflection.
Do not start building from here — a pitch that has not been bet on goes to the PO, not to
/build.
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.
- 3d ago First seen · 13 lines · 18 tokens per session scan A f9ca71ee2463
shape is a command published in the GitHub repository nguyenvanphituoc/shapeup-sdlc-plugin (2 stars, last pushed 13d ago), licensed MIT. It adds 18 tokens to every session and 161 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 2026-08-31.
Other commands, from other repositories
project
Generate project documentation (product.md, structure.md, tech.md, codemaps/).
toh-help
Display all Toh Framework commands and quick usage guide.
feature
Create a feature specification using spec-driven development.
deep-audit.skeleton
Aciklama: Bu bolum Bootstrap tarafindan manifest verileriyle doldurulur. Gerekli manifest alanlari: project.description, stack.primary, project.structure, project.subprojects, stack.orm, stack.authmethod Ornek cikti.
fix-issue
!gh issue view $ARGUMENTS 2>/dev/null || echo "Could not fetch issue $ARGUMENTS".
rev
Invoke Code Reviewer for code quality, security, requirements validation, and best practices review.