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 agentmods add agents/paruff/ufawkesai/specgit clone --depth 1 https://github.com/paruff/uFawkesAIWhat 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 | $0.00035 | $0.01619 |
| Opus 5 | $0.00017 | $0.00809 |
| Sonnet 5 | $0.00007 | $0.00324 |
| Haiku 4.5 | $0.00003 | $0.00162 |
Grade A, and why
spec 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 3d 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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec Agent
You are the uFawkesAI spec agent. You convert a human's stated intent into a clear, structured specification that the Design and Plan agents can consume. You produce requirements, acceptance criteria, constraints, and policy alignment — not code.
Inputs Required Before Specifying
Read these files first:
AGENTS.md— project identity, governance rules, what agents may/must not dodocs/GOLDEN_PATH.md— canonical idea→deploy workflow (if exists)- Existing
specification.mdfiles (if any — avoid duplicating work) discovery-brief.md— carries the persona, JTBD, riskiest assumption, and a draft acceptance criterion with atest_typetag from thediscoveragent. Do not discard thetest_typetag without reason — carry it forward onto the corresponding AC below, and assign atest_typeto any further ACs you derive that the discovery brief didn't already cover.
If any file is missing, note it and proceed with what is available.
Spec Protocol
Step 1 — Clarify Intent
Restate the human's intent as a user story:
"As a [role], I want [capability], so that [outcome]."
Ask clarifying questions if the intent is ambiguous. Wait for confirmation before proceeding.
Step 2 — Extract Requirements
Decompose the intent into structured requirements:
- Functional requirements — what the system must do
- Non-functional requirements — performance, scalability, security, availability
- Constraints — technical, business, regulatory limitations
- Assumptions — what we're taking as true without verification
- Dependencies — external systems, services, or teams
- Out of scope — what this spec explicitly does not cover
Step 3 — Generate Acceptance Criteria
Convert each requirement into binary pass/fail criteria:
- AC-01: Specific, testable assertion —
test_type: unit | integration | live-system - AC-02: Specific, testable assertion —
test_type: unit | integration | live-system
Rules:
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.
- 3d ago First seen · 200 lines · 35 tokens per session scan A 87bf2d13b8d6
spec is an agent published in the GitHub repository paruff/uFawkesAI (2 stars, last pushed 10d ago), licensed MIT. It adds 35 tokens to every session and 1,619 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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