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 userInner/SKILLS --skill intent-driven-development-affaan-m-eccgit clone --depth 1 https://github.com/userInner/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/userinner/skills/intent-driven-development-affaan-m-ecc)<a href="https://agentmods.dev/skills/userinner/skills/intent-driven-development-affaan-m-ecc"><img src="https://agentmods.dev/badge/skills/userinner/skills/intent-driven-development-affaan-m-ecc/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/userinner/skills/intent-driven-development-affaan-m-ecc"><img src="https://agentmods.dev/badge/skills/userinner/skills/intent-driven-development-affaan-m-ecc.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 | $0.00098 | $0.03400 |
| Opus 5 | $0.00049 | $0.01700 |
| Sonnet 5 | $0.00020 | $0.00680 |
| Haiku 4.5 | $0.00010 | $0.00340 |
Grade A, and why
intent-driven-development 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 7d 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.
This is a copy
89% identical to intent-driven-development — 30 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Intent-Driven Development
Produce useful acceptance criteria without turning specification into ceremony. Inspect available context first, expose genuine ambiguity, and choose verification methods that fit the work and its risk.
When to Activate
- User asks to clarify a feature, define acceptance criteria, or de-risk a change before implementation
- Request touches security, authentication, persistent data, migrations, external APIs, or compliance
- User wants to prepare a handoff artifact for another agent or team
- Request is ambiguous enough that the expected outcome is not yet observable or testable
- User explicitly invokes this skill with
/intent-driven-development
Do not activate for trivial edits, straightforward one-line fixes, active debugging sessions, code review requests, or implementation requests whose acceptance conditions are already clear.
How It Works
- Inspect context first — reads the repository, docs, schemas, and test infrastructure for technical facts before asking any question, while treating product/business constraints as something only the user or a product artifact can supply
- Choose depth — selects Quick Capture (3-7 criteria, low/moderate risk) or Full Acceptance Brief (security, data, migration, cross-system changes) based on the risk profile
- Ask minimally — only asks questions whose answers cannot be inferred and that materially change scope or behavior
- Write observable criteria — each AC-NNN describes a starting condition, trigger, expected outcome, prohibited side effect, verification method, and priority; no vague words like "correctly" or "securely" without evidence
- Proceed or hand off — for clear requests with no blocking risks, records criteria and continues; for risky changes, presents blockers and waits for confirmation
- Handle revision — if an AC fails mid-implementation due to architectural constraints, marks it
[revised], updates scope or verification method, increments the revision number, and re-presents only the changed criteria
What ships with it
3 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.
- 7d ago First seen · 361 lines · 98 tokens per session scan A e34045f7b3bf
intent-driven-development is a skill published in the GitHub repository userInner/SKILLS (3 stars, last pushed 3d ago), licensed Apache-2.0. It adds 98 tokens to every session and 3,400 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to intent-driven-development, differing in 30 lines, and is treated as a copy.
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