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 dayfinggg/openai-codex-agent-skills --skill specifygit clone --depth 1 https://github.com/dayfinggg/openai-codex-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/dayfinggg/openai-codex-agent-skills/specify)<a href="https://agentmods.dev/skills/dayfinggg/openai-codex-agent-skills/specify"><img src="https://agentmods.dev/badge/skills/dayfinggg/openai-codex-agent-skills/specify/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/dayfinggg/openai-codex-agent-skills/specify"><img src="https://agentmods.dev/badge/skills/dayfinggg/openai-codex-agent-skills/specify.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 | $0.00045 | $0.00417 |
| Opus 5 | $0.00023 | $0.00209 |
| Sonnet 5 | $0.00009 | $0.00083 |
| Haiku 4.5 | $0.00005 | $0.00042 |
Grade A, and why
specify 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 2d 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 — 31 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Specify
Follow the governing instructions and the user's requirements for communication, code style, authorization, and delegation. This skill supplies task-specific guidance, not permission to expand the task. Its workflow and output fields describe internal checks and relevant content, not a mandatory response layout or a progress report. When used within broader authorized work, continue that work through completion rather than stopping to deliver this skill's intermediate result.
Synthesize what is already known. Do not restart discovery or invent missing product decisions.
Establish the source
Use the current conversation, linked issue, accepted decisions, and relevant project evidence. Mark unresolved material as an open question. If one missing decision prevents a coherent contract, ask only that question.
Define the contract
State the problem, users or callers, desired behavior, inputs, outputs, state transitions, error behavior, compatibility constraints, and non-functional requirements that affect implementation. Express acceptance criteria as observable outcomes.
Cover successful, boundary, and failure cases. Resolve ambiguous business terms and keep stable business behavior separate from volatile UI or implementation detail. When several roles own the contract, use available accepted decisions and identify genuinely missing requirements. Do not invent a mandatory stakeholder review or contact other people unless the task requires and authorizes it.
Keep implementation choices only when they are already decided or required by the repository. Separate product requirements from implementation notes. Name what is out of scope so downstream work does not expand silently.
Quality check
Confirm that every requirement is testable, terms are consistent, conflicts are surfaced, and no acceptance criterion depends on an undefined concept. Remove duplicated background and speculative features.
Output
Return a concise specification with problem, behavior, acceptance criteria, constraints, out-of-scope items, open questions, and supporting evidence. Write to an external tracker or file only when the request authorizes that write.
What ships with it
1 file 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.
- 2d ago Changed · +2 lines 32096fcbdda9
- 4d ago Changed · +2 lines b2f9b707e9f9
- 9d ago First seen · 27 lines · 45 tokens per session scan A 1f97b9ac4c5a
specify is a skill published in the GitHub repository dayfinggg/openai-codex-agent-skills (4 stars, last pushed 3d ago), licensed MIT. It adds 45 tokens to every session and 417 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.
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Systematic review response workflow from comment analysis to professional rebuttal writing. Use when the user asks to "write rebuttal", "respond to reviewers", "draft review response", or "analyze review comments". Improves paper acceptance rates.
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