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 Avyayalaya/agent-prime --skill specification-writinggit clone --depth 1 https://github.com/Avyayalaya/agent-primeWrote 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/avyayalaya/agent-prime/specification-writing)<a href="https://agentmods.dev/skills/avyayalaya/agent-prime/specification-writing"><img src="https://agentmods.dev/badge/skills/avyayalaya/agent-prime/specification-writing/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/avyayalaya/agent-prime/specification-writing"><img src="https://agentmods.dev/badge/skills/avyayalaya/agent-prime/specification-writing.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 | $0.00056 | $0.25153 |
| Opus 5 | $0.00028 | $0.12576 |
| Sonnet 5 | $0.00011 | $0.05031 |
| Haiku 4.5 | $0.00006 | $0.02515 |
Grade A, and why
specification-writing 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- specification-writing — 86% identical, 80 lines differ
How it starts
The opening of the file, as written. The whole thing — 1,591 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Produce a Zero-Question Specification — a spec so complete that any competent executor (AI agent, engineer, contractor, cross-functional team) can begin work immediately without asking a single clarifying question.
A Zero-Question Spec is not the same as a long spec. Length is a symptom, not a goal. The goal is that every assumption is surfaced, every ambiguity is resolved or explicitly marked TBD with an owner and deadline, every acceptance criterion is binary-testable, and every scope boundary names the adjacent capability it excludes.
This codex encodes six interlocking frameworks that systematize the transition from "rough feature intent" to "executable specification." Each framework targets a specific class of spec failure. Together, they eliminate the five most common causes of execution failure: unclear outcomes, untestable criteria, invisible scope creep, missing executor context, and silent assumptions.
When to Use / When NOT to Use
When to Use
- Writing a product or feature spec for a new user-facing capability
- Writing an API contract spec that multiple teams or services will implement against
- Writing an agent task spec for an AI agent that will execute autonomously
- Writing a process or workflow spec that crosses team boundaries
- Writing an infrastructure or migration spec where failure conditions are critical
- Writing a research or discovery spec where "done" is ambiguous without explicit criteria
- Upgrading a draft spec that has already generated clarifying questions from executors
- Reviewing an existing spec for completeness before handing off to execution
When NOT to Use
- Brainstorming or ideation — this skill assumes you already know WHAT to build; if you don't, use Problem Framing or Discovery first
- One-line tickets for well-understood changes — if the executor already has full context and the change is trivial (e.g., "change button color from blue to green"), a zero-question spec is overhead
- Exploratory prototypes with no success criteria — if the goal is "try things and see what works," a spec constrains prematurely. Use a time-boxed spike instead.
- Post-hoc documentation — this skill is for BEFORE execution, not for documenting what was already built
- Specs where the audience is exclusively yourself — the frameworks are calibrated for context transfer to another executor. If you are the sole executor and have full context, a lighter checklist may suffice.
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 · 1,591 lines · 56 tokens per session scan A 23e4fd937c0d
specification-writing is a skill published in the GitHub repository Avyayalaya/agent-prime (8 stars, last pushed 3mo ago), licensed MIT. It adds 56 tokens to every session and 25,153 once invoked, about $0.0003 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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