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 skills/tienenwu/fables/feature-flownpx skills add tienenwu/fables --skill feature-flowgit clone --depth 1 https://github.com/tienenwu/fablesWrote 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/tienenwu/fables/feature-flow)<a href="https://agentmods.dev/skills/tienenwu/fables/feature-flow"><img src="https://agentmods.dev/badge/skills/tienenwu/fables/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 | $0.00035 | $0.01171 |
| Opus 5 | $0.00017 | $0.00585 |
| Sonnet 5 | $0.00007 | $0.00234 |
| Haiku 4.5 | $0.00003 | $0.00117 |
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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🌐 繁體中文（canonical） · English mirror
feature-flow — Harness high-risk-feature Profile
Core Principles
This skill supplies spec/design/implementation techniques and artifact templates for high-risk features. When Harness exists, Harness owns risk routing, state transitions, evidence, and contract lifecycle. This skill never creates a second state machine.
Without Harness, use the same profile after creating a risk assessment and one artifact root: docs/plans/<slug>/.
When to Use
Use for public APIs, schemas, shared integration points, cross-layer data flow, migrations, releases, auth/payments/production data, or features with both costly ambiguity and rollback.
Do not use merely because many files change. Low-risk mechanical changes use quick/standard. If design has no material tradeoff and no absolute escalation trigger, return to the risk router and downgrade.
Profile States
1. Discovery / Risk
Add Risk Assessment to plan.md: matched absolute high-risk triggers, why quick conditions do not all hold, matching contracts, reusable patterns, external side effects, and verification limits. Do not total numeric scores.
File count records blast radius but never selects the profile alone.
2. Spec
Create spec.md: Why, in/out scope, GIVEN-WHEN-THEN AC, assumptions, non-goals, and rollback conditions.
Ask the user only for costly ambiguity, product/scope tradeoffs, public contracts, irreversible actions, or external side effects. Decide reversible internals and record assumptions.
UI/UX ambiguity requires a mockup, walkthrough, or annotated screenshot before implementation.
3. Design / Plan
Create plan.md: architecture/data flow, Key Decisions, interfaces, migration/rollback, phases, phase acceptance, and planned evidence for every AC.
Every phase must be independently verifiable. Split phases that span unrelated risk surfaces. Prefer established adjacent patterns over generic design.
What ships with it
2 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.
- 4d ago First seen · 93 lines · 35 tokens per session scan A 21f4108a857a
feature-flow is a skill published in the GitHub repository tienenwu/fables (4 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 1,171 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.
Other skills, from other repositories
speckit-specify
Create or update the feature specification from a natural language feature description.
speckit-analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
docs-build
Build, preview, and validate the Uno documentation website (DocFX) locally — surface real content errors vs expected noise, drive rendered pages with Playwright, and validate external-doc commit bumps in importexternaldocs.ps1 before a PR. Use when working under doc/, editing articles/ markdown, bumping an external…
speckit-taskstoissues
Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design artifacts.
speckit-git-feature
Create a feature branch with sequential or timestamp numbering.
speckit-git-remote
Detect Git remote URL for GitHub integration.