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 mini-specgit 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/mini-spec)<a href="https://agentmods.dev/skills/tmusser/ai-engineering-skills/mini-spec"><img src="https://agentmods.dev/badge/skills/tmusser/ai-engineering-skills/mini-spec/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/mini-spec"><img src="https://agentmods.dev/badge/skills/tmusser/ai-engineering-skills/mini-spec.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 | $0.00040 | $0.01053 |
| Opus 5 | $0.00020 | $0.00526 |
| Sonnet 5 | $0.00008 | $0.00211 |
| Haiku 4.5 | $0.00004 | $0.00105 |
Grade A, and why
mini-spec 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 9d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mini Spec
Purpose
Create the smallest useful SPEC.md that clarifies intent, names the likely failure mode, and gives the agent a verifiable target before planning or implementation.
The spec is both a floor and a ceiling: acceptance criteria define what must happen; non-goals, constraints, and invalid-if rules bound what must not be added.
When a high-fidelity reference already expresses behavior well, point to it instead of rewriting it into a weaker prose summary. The spec should capture the task-specific delta, authority boundary, and proof target around that reference.
When to use
Use when a project or feature is clear enough to define before implementation.
Inputs
- Clarified request
CONTEXT.mdif available- Constraints
- Known commands
- Acceptance criteria or desired behavior
- Authoritative references when available: existing tests, code, schemas, HTML/mockups, rubrics, external specs, or a source implementation to port
Reference-first rule
Prefer the richest authoritative source that already expresses the intended behavior.
For each reference, record:
- the exact file, test, artifact, URL, or symbol
- what behavior or decision it governs
- the task-specific delta, if this slice intentionally differs
Do not restate a detailed test suite, implementation, mockup, or rubric line by line merely to make the spec self-contained. Keep the reference available and write only the interpretation needed to bound this task.
If the user request and an authoritative reference conflict, surface the conflict as an explicit decision or open question. Do not silently reconcile them.
Workflow
- State the objective.
- Identify the user or use case.
- Identify authoritative references and what each one governs.
- Record the task-specific delta from those references; use
nonewhen the reference is the intended contract as-is. - Define observable acceptance criteria, pointing to authoritative references where they already encode the behavior precisely.
- Record non-goals.
- Define the spec ceiling: do not add behavior, interfaces, refactors, dependencies, or adjacent cleanup beyond what is required to satisfy the acceptance criteria and reference-backed delta.
- List likely failure modes and name the primary failure mode for this slice.
- Record constraints.
- List only non-obvious run, test, build, and verification commands that matter to the slice.
- Define the smallest verification demo.
- Record open questions and reference conflicts instead of inventing a resolution.
- When applicable, name compatibility seams that must remain import-compatible or output-compatible.
- When applicable, record invalid-if constraints that would make the slice non-viable.
- For delegated, autonomous, multi-session, or replanned work, optionally record a contract ID, parent ID, base commit, issue time, and replan reason.
- If satisfying the task requires behavior outside the ceiling or contradicts an authoritative reference, update or renegotiate the spec before implementing that expansion.
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.
- 9d ago First seen · 112 lines · 40 tokens per session scan A 81eb29f6eeb0
mini-spec is a skill published in the GitHub repository tmusser/ai-engineering-skills (4 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 1,053 once invoked, about $0.0002 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.