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 dcosson/h2 --skill shapinggit clone --depth 1 https://github.com/dcosson/h2Wrote 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/dcosson/h2/shaping)<a href="https://agentmods.dev/skills/dcosson/h2/shaping"><img src="https://agentmods.dev/badge/skills/dcosson/h2/shaping/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/dcosson/h2/shaping"><img src="https://agentmods.dev/badge/skills/dcosson/h2/shaping.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00030 | $0.05586 |
| Opus 5.5 | $0.00012 | $0.02234 |
| Sonnet 5.5 | $0.00006 | $0.01117 |
| Haiku 4.5 | $0.00003 | $0.00559 |
Grade A, and why
shaping 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- shaping — 100% identical, 147 lines differ
How it starts
The opening of the file, as written. The whole thing — 625 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shaping Methodology
A structured approach for collaboratively defining problems and exploring solution options.
Multi-Level Consistency (Critical)
Shaping produces documents at different levels of abstraction. Truth must stay consistent across all levels.
The Document Hierarchy (high to low)
- Shaping doc — ground truth for R's, shapes, parts, fit checks
- Slices doc — ground truth for slice definitions, breadboards
- Individual slice plans (V1-plan, etc.) — ground truth for implementation details
The Principle
Each level summarizes or provides a view into the level(s) below it. Lower levels contain more detail; higher levels are designed views that help acquire context quickly.
Changes ripple in both directions:
- Change at high level → trickles down: If you change the shaping doc's parts table, update the slices doc too.
- Change at low level → trickles up: If a slice plan reveals a new mechanism or changes the scope of a slice, the Slices doc and shaping doc must reflect that.
The Practice
Whenever making a change:
- Identify which level you're touching
- Ask: "Does this affect documents above or below?"
- Update all affected levels in the same operation
- Never let documents drift out of sync
The system only works if the levels are consistent with each other.
Starting a Session
When kicking off a new shaping session, offer the user both entry points:
- Start from R (Requirements) — Describe the problem, pain points, or constraints. Build up requirements and let shapes emerge.
- Start from S (Shapes) — Sketch a solution already in mind. Capture it as a shape and extract requirements as you go.
There is no required order. Shaping is iterative — R and S inform each other throughout.
Working with an Existing Shaping Doc
When the shaping doc already has a selected shape:
- Display the fit check for the selected shape only — Show R × [selected shape] (e.g., R × F), not all shapes
- Summarize what is unsolved — Call out any requirements that are Undecided, or where the selected shape has ❌
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.
- 1mo ago First seen · 625 lines · 30 tokens per session scan A 2ea9742ecfe3
shaping is a skill published in the GitHub repository dcosson/h2 (163 stars, last pushed yesterday), licensed MIT. It adds 30 tokens to every session and 5,586 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.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…