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 fiveonecode/agent-skills --skill spec-creation-updatinggit clone --depth 1 https://github.com/fiveonecode/agent-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/fiveonecode/agent-skills/spec-creation-updating)<a href="https://agentmods.dev/skills/fiveonecode/agent-skills/spec-creation-updating"><img src="https://agentmods.dev/badge/skills/fiveonecode/agent-skills/spec-creation-updating/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/fiveonecode/agent-skills/spec-creation-updating"><img src="https://agentmods.dev/badge/skills/fiveonecode/agent-skills/spec-creation-updating.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 | $0.00064 | $0.00930 |
| Opus 5.5 | $0.00026 | $0.00372 |
| Sonnet 5.5 | $0.00013 | $0.00186 |
| Haiku 4.5 | $0.00006 | $0.00093 |
Grade A, and why
spec-creation-updating 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.
How it starts
The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec Creation Updating
Overview
Produce specs that reduce ambiguity and can be implemented with minimal back-and-forth. Apply this workflow to any project domain (product, backend, API, data, UI, infrastructure, ops).
Workflow
1. Set boundaries
- Capture the objective and user/business value.
- Define in-scope and out-of-scope behavior.
- Record assumptions, dependencies, and constraints.
- Ask clarifying questions when decisions affect architecture, cost, security, or user-visible behavior.
2. Choose depth
- Write a lightweight spec for isolated, low-risk changes.
- Write a full system spec for cross-team, risky, or high-impact work.
- Keep the same quality gates regardless of depth.
3. Build structure
- Start from
references/spec-template.md. - Preserve repository naming, section ordering, and style if they already exist.
- Add domain-specific sections as needed, but do not remove mandatory content.
4. Fill concrete requirements
- Write requirements as testable statements, not intentions.
- Define success paths, edge cases, and failure behavior.
- Specify interfaces, data contracts, and state transitions when relevant.
- Specify non-functional requirements: performance, reliability, scalability, observability.
- When work spans existing code paths, add an implementation map that names the canonical files or directories to edit and adjacent paths that must remain untouched. Keep the map aligned with the repository's real structure so an implementer does not have to infer sibling paths from prose.
- For external, generated, AI-facing, or verifier-owned contracts, add a machine-checkable contract block before implementation details.
5. Define verification and completion
- Map each requirement to a verification method.
- Bind every requirement to a concrete verifier, test, or manual check ID; bind every verifier back to the requirement it proves.
- Include reproducible commands, tests, and manual checks when automation is unavailable.
- Define completion criteria with pass/fail outcomes.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 100 lines · 64 tokens per session scan A 2bd124f357b4
spec-creation-updating is a skill published in the GitHub repository fiveonecode/agent-skills (19 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 930 once invoked, about $0.0003 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.
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