Borrowing it
Nothing to install: this file belongs to PedroMosquera/squadai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/PedroMosquera/squadai/main/.claude/skills/sdd/sdd-apply/SKILL.mdgit clone --depth 1 https://github.com/PedroMosquera/squadaiWrote 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/pedromosquera/squadai/sdd-apply)<a href="https://agentmods.dev/skills/pedromosquera/squadai/sdd-apply"><img src="https://agentmods.dev/badge/skills/pedromosquera/squadai/sdd-apply/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/pedromosquera/squadai/sdd-apply"><img src="https://agentmods.dev/badge/skills/pedromosquera/squadai/sdd-apply.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 | $0.00014 | $0.00557 |
| Opus 5 | $0.00007 | $0.00279 |
| Sonnet 5 | $0.00003 | $0.00111 |
| Haiku 4.5 | $0.00001 | $0.00056 |
Grade A, and why
sdd-apply 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SDD Apply Skill
Implement exactly what the specification says. No more, no less. This skill is used by the Implementer after the Spec Writer and Designer have produced their artifacts.
Core Principle
Your job is to implement what is specified, not to improve the design. If the spec is wrong, report it — do not fix it silently.
Steps
-
Read the full spec before writing any code: Understand the complete interface contract before starting the first function.
- Note all invariants and error conditions
- Mark any ambiguities to report back to the orchestrator
-
Implement interfaces first: Create types and method stubs before logic.
- Implement all interface methods (even stubs return placeholder errors)
- This ensures compilation and enables parallel work by others
- Run
go build ./...after stubs are in place
-
Implement one spec item at a time: Work through the spec sequentially.
- Pick one function or behavior from the spec
- Write a test for it (even in SDD, tests validate spec compliance)
- Implement it
- Verify the test passes
-
Respect the interface contract strictly:
- Return exactly the error types specified — no substitutions
- Produce exactly the output format specified
- Respect all invariants stated in the spec
- If spec says "side effect X happens", make it happen
-
Handle all edge cases in the spec:
- Check the "Edge Case Behavior" table in the spec
- Each row must be implemented
- Do not add undocumented behavior
-
Do not add extras:
- No logging unless specified
- No caching unless specified
- No additional validation beyond what is specified
- No convenience methods not in the interface
-
Report spec gaps: If you encounter behavior the spec does not cover:
- Do not guess — make a conservative implementation (return error)
- Document the gap explicitly with a
// TODO(spec): ...comment - Report gaps to the orchestrator before finalizing
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 · 73 lines · 14 tokens per session scan A aa349d5b1d96
sdd-apply is a skill published in the GitHub repository PedroMosquera/squadai (8 stars, last pushed 1mo ago), licensed MIT. It adds 14 tokens to every session and 557 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
harness-engineering
Use when the user asks to improve, fix, or build their repository's AI harness — AGENTS.md, rules, skills, commands, hooks, guardrails, CI sensors — or to act on harness-score audit findings and raise their maturity level.
reap
Report how much of the context this agent loads is never used - unused skills, MCP servers, subagents, hooks and always-loaded prose - measured from real session transcripts. Use when asked why the context window is full, what is wasting tokens, or what is safe to remove.
gap
Measure the loaded-versus-fired gap - what fraction of each category of loaded context is ever actually invoked, and which MCP tools return mostly noise. Use when asked how much of the context is earning its place, or which categories are worst.
replay
Find, analyze, and share AI coding sessions with vibe-replay. Use when the user asks for a replay, wants to find a past session, run a session retro, share Cursor/Claude/Codex session context, or attach session context to a PR.
skill-doctor
Use the skill-doctor CLI or UI to inspect and manage AI-agent skills, rules, instructions, MCP resources, and context cost across supported platforms. Trigger when the user asks to scan or audit agent skills, find duplicates or trigger conflicts, investigate unsafe instructions, estimate context-token cost, compare…
skill-doctor-context-optimizer
Interactively keep the skills, MCP servers/tools, and plugins relevant to the user's current task, preview project-local disables for the rest, apply only explicitly confirmed controls through skill-doctor, and report approximate context-token savings. Trigger when the user asks to slim, optimize, prune, or reduce the…