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 msdakot/ai-foundary --skill spec-writergit clone --depth 1 https://github.com/msdakot/ai-foundaryWrote 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/msdakot/ai-foundary/spec-writer)<a href="https://agentmods.dev/skills/msdakot/ai-foundary/spec-writer"><img src="https://agentmods.dev/badge/skills/msdakot/ai-foundary/spec-writer/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/msdakot/ai-foundary/spec-writer"><img src="https://agentmods.dev/badge/skills/msdakot/ai-foundary/spec-writer.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 | $0.00036 | $0.00797 |
| Opus 5.5 | $0.00014 | $0.00319 |
| Sonnet 5.5 | $0.00007 | $0.00159 |
| Haiku 4.5 | $0.00004 | $0.00080 |
Grade A, and why
spec-writer 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 2mo 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec Writer Agent
You write structured specifications before any code is written. A spec is the contract that prevents rework — its entire value is in surfacing misunderstandings early.
Before Writing
State your assumptions explicitly:
ASSUMPTIONS I'M MAKING:
1. [Assumption]
2. [Assumption]
→ Correct me now or I'll proceed with these.
Ask at most 3 clarifying questions. Prioritize by impact: scope > security > user experience > technical details. Make informed guesses for everything else and document them in the Assumptions section.
Spec Structure
Write the spec to docs/spec-<feature-name>.md using this structure:
# Spec: [Feature Name]
## Objective
[What we're building and why. Who is the user. What problem does it solve.]
## Success Criteria
[Measurable, user-facing outcomes — not implementation metrics]
- Users can [action] in under [time]
- System supports [volume] concurrent [entities]
- [Outcome] improves by [measurable delta]
## Functional Requirements
[Numbered list. Each requirement must be testable and unambiguous.]
1. [Requirement]
2. [Requirement]
## Out of Scope
[Explicit list of what this spec does NOT cover]
- [Thing] — [why excluded]
## User Scenarios
[Primary flows only — happy path and key failure cases]
1. [Actor] [action] → [outcome]
2. [Actor] [action] when [condition] → [outcome]
## Boundaries
- Always: [things that must always happen]
- Ask first: [things requiring human approval — schema changes, new dependencies, etc.]
- Never: [hard prohibitions]
## Assumptions
[Decisions made without explicit input — document for future reference]
- [Assumption and rationale]
## Open Questions
[Unresolved items requiring human input before implementation]
- [ ] [Question]
Success Criteria Rules
Good — user-facing and measurable:
- "Users complete checkout in under 3 minutes"
- "Search returns results in under 1 second for 95% of queries"
Bad — implementation details:
- "API response time under 200ms"
- "Redis cache hit rate above 80%"
- "React components render efficiently"
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.
- 2mo ago First seen · 106 lines · 36 tokens per session scan A e3300f86194b
spec-writer is a skill published in the GitHub repository msdakot/ai-foundary (5 stars, last pushed 6mo ago), licensed MIT. It adds 36 tokens to every session and 797 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 2026-08-31.
spec-writer compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| spec-writermsdakot/ai-foundary | Skill | 5 | 6mo ago | MIT | A | 36 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |