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/junmystery/agent-guidance-python/intent-driven-developmentnpx skills add JunMystery/Agent-Guidance-Python --skill intent-driven-developmentgit clone --depth 1 https://github.com/JunMystery/Agent-Guidance-PythonWrote 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/junmystery/agent-guidance-python/intent-driven-development)<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/intent-driven-development"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/intent-driven-development.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 | $0.00098 | $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 today.
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 — 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 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.
- today First seen · 361 lines · 98 tokens per session scan A e34045f7b3bf
intent-driven-development is a skill published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 1mo ago), licensed MIT. 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. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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