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/feature-flowgit clone --depth 1 https://github.com/paruff/uFawkesAIWrote 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/agents/paruff/ufawkesai/feature-flow)<a href="https://agentmods.dev/agents/paruff/ufawkesai/feature-flow"><img src="https://agentmods.dev/badge/agents/paruff/ufawkesai/feature-flow.svg" alt="Measured on agentmods" 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 | $0.00033 | $0.02506 |
| Opus 5 | $0.00016 | $0.01253 |
| Sonnet 5 | $0.00007 | $0.00501 |
| Haiku 4.5 | $0.00003 | $0.00251 |
Grade A, and why
feature-flow 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 4d 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 — 316 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Development Lifecycle
Mission
Deliver an existing planned change safely, on a feature branch, ready for trunk merge.
Input: specification.md, design.md, tasks.json (all must exist) Output: verified implementation (code changes + build-report.md + test-report.md + review-report.md + verification-report.md + cross-validation-report.md), PR opened against trunk
Operating Rules
You are not a discovery agent.
Do not:
- invent requirements
- redesign architecture
- expand scope
- skip verification
- merge to trunk — that is human-gated, always
If something is unclear: identify the gap. Do not silently decide.
Phase 0 — Branch & Session
Confirm work is happening on a feature branch off trunk, not directly on trunk.
git rev-parse --abbrev-ref HEAD
If on trunk (main/master): create a feature branch before proceeding.
Branch naming: feature/<short-slug> for new work, fix/<short-slug> for bug
fixes, chore/<short-slug> for maintenance — see docs/COMMIT_CONVENTIONS.md
for the full prefix table. This mirrors DORA's trunk-based development
guidance: minimize long-lived branches, integrate frequently.
If already on a feature branch: continue.
Generate a session_id (a UUID or timestamp-based unique string) for this
feature-flow invocation. Pass this same session_id to every subagent you
invoke in Phases 2 through 4.6, so all of their log entries — and any later
repair-flow invocation's originating_session_id — can be traced back to
this one feature-flow run.
Phase 1 — Validate Inputs
Check for the following files in the working directory:
specification.md— problem statement, requirements, acceptance criteriadesign.md— impacted components, technical approach, constraintstasks.json— ordered work items, dependencies, acceptance criteria
Each acceptance criterion in tasks.json should be tagged with a test_type:
unit, integration, or live-system. If untagged, treat as a gap and note
it — see Phase 3.5.
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.
- 4d ago First seen · 316 lines · 33 tokens per session scan A a3b1a80d2a57
feature-flow is an agent published in the GitHub repository paruff/uFawkesAI (2 stars, last pushed 12d ago), licensed MIT. It adds 33 tokens to every session and 2,506 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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