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 tmusser/ai-engineering-skills --skill thin-plangit clone --depth 1 https://github.com/tmusser/ai-engineering-skillsWrote 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/tmusser/ai-engineering-skills/thin-plan)<a href="https://agentmods.dev/skills/tmusser/ai-engineering-skills/thin-plan"><img src="https://agentmods.dev/badge/skills/tmusser/ai-engineering-skills/thin-plan/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/tmusser/ai-engineering-skills/thin-plan"><img src="https://agentmods.dev/badge/skills/tmusser/ai-engineering-skills/thin-plan.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 | $0.00016 | $0.00309 |
| Opus 5 | $0.00008 | $0.00154 |
| Sonnet 5 | $0.00003 | $0.00062 |
| Haiku 4.5 | $0.00002 | $0.00031 |
Grade A, and why
thin-plan 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.
What it actually says
Thin Plan
Purpose
Convert the mini-spec into 3-7 vertical implementation slices.
When to use
Use when SPEC.md exists and implementation needs a short, ordered path.
Inputs
SPEC.mdCONTEXT.md- Existing repo structure
- Available verification commands
Workflow
- If
SPEC.mdhas an active Contract ID, copy that ID exactly intoPLAN.md. Do not invent an ID when SPEC has none. - Identify the smallest end-to-end behavior.
- Create 3-7 slices that each produce observable behavior.
- Make every slice independently verifiable.
- Keep each slice to the fewest files possible.
- Avoid horizontal architecture-only tasks unless required.
- Record dependencies, risks, and verification strategy.
- Write
PLAN.mdandTODO.md.
Outputs
PLAN.mdTODO.md- Active Contract ID in
PLAN.mdonly when SPEC opted into contract identity
Stop conditions
- Each task has a visible result and a check.
- Planning reveals a missing spec decision.
Anti-patterns
- Planning all backend, then all frontend, then all tests.
- Creating broad tasks that cannot be finished in one session.
- Treating setup work as progress when no behavior changes.
- Inventing contract identity for work whose SPEC did not opt in.
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 · 51 lines · 16 tokens per session scan A 414700479f5e
thin-plan is a skill published in the GitHub repository tmusser/ai-engineering-skills (4 stars, last pushed yesterday), licensed MIT. It adds 16 tokens to every session and 309 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 skills, from other repositories
awsl
Run Claude Code JavaScript Workflows through the awsl compatibility runtime. Use when an agent's current task or loaded Skill requires dispatching a Claude Code Workflow but the host cannot execute that Workflow natively, or when awsl workflow inspection, durable run state, resume, or provider diagnostics are needed.
dwi-all-in-one
Apply the relevant Dwi lenses together when several observed workflow problems co-occur. Select only the lenses the task needs, preserve a silent fast path for clear reversible work, and keep authority and evidence explicit. Prefer a focused module when one issue dominates.
dwi-arc
Structure genuinely multi-agent coding work into bounded cells with one writer per scope, explicit integration, and independent review. Use when several disjoint workstreams justify coordination. Do not use for small tasks, overlapping writers, speculative agent fleets, or process artifacts without demonstrated value.
dwi-bridge
Coordinate bounded work between native Claude and Codex workflows with explicit authority, scope, and evidence. Use for read-only consultation or explicitly authorized execution delegation. Do not create a new connector, share secrets, treat messages as authorization, or allow recursive delegation.
dwi-budget
Set and report practical token, context, time, tool-call, and coordination boundaries for coding-agent work. Use when resource use is unclear or needs a checkpoint. Do not invent measurements, monetary savings, cache benefit, or precision that the harness does not expose.
dwi-evidence
Label coding-agent claims by evidence status, preserve provenance and failures, and separate static, runtime, and human proof. Use before completion, comparison, promotion, or handoff. Do not upgrade observations into guarantees or fabricate missing measurements and approvals.