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.
git clone --depth 1 https://github.com/naimkatiman/continuous-improvementWrote 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/commands/naimkatiman/continuous-improvement/intent-driven-development)<a href="https://agentmods.dev/commands/naimkatiman/continuous-improvement/intent-driven-development"><img src="https://agentmods.dev/badge/commands/naimkatiman/continuous-improvement/intent-driven-development/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/commands/naimkatiman/continuous-improvement/intent-driven-development"><img src="https://agentmods.dev/badge/commands/naimkatiman/continuous-improvement/intent-driven-development.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 | $0.00061 | $0.00494 |
| Opus 5.5 | $0.00024 | $0.00198 |
| Sonnet 5.5 | $0.00012 | $0.00099 |
| Haiku 4.5 | $0.00006 | $0.00049 |
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 1mo 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.
What it actually says
/intent-driven-development
Convert an ambiguous or high-impact request into observable acceptance criteria before you build, so "done" is a fact two people would agree on and the agreed plan is held sacred (Law 2). Produce useful criteria without ceremony: inspect context first, expose only genuine ambiguity, choose verification that fits the risk.
Trigger phrases
/intent-driven-development/intent-driven-development <the change>- "define acceptance criteria"
- "scope this change" / "make this testable"
- "de-risk this before we build it"
- "prepare implementation requirements for another agent"
Do not trigger for trivial edits, one-line fixes, active debugging, code review, or requests whose acceptance conditions are already clear.
What happens
- Inspect and scope. Read the repo, docs, schemas, and tests for technical facts before asking. Capture product or business constraints only from the user or a product artifact, never inferred from code.
- Choose depth. Quick Capture (3-7 criteria, low or moderate risk) or Full Acceptance Brief (security, data, migration, cross-system, or handoff).
- Write criteria. Each
AC-NNNnames a scenario, a trigger, an expected observable result, a prohibited side effect when meaningful, a verification method, and a priority. No vague words without defined evidence. - Proceed or hand off. Record the criteria and continue for a clear request; present blockers and wait when a change is risky. If a criterion cannot be met mid-build, mark it
[revised], increment the revision, and re-present only the changed criteria.
Skill file
Full behavior is defined in skills/intent-driven-development.md.
Pairs with
/grill-me: grill-me clarifies a fuzzy input; this skill turns the agreed intent into verifiable criteria./roast: roast validates the idea, then scope the survivor into acceptance 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.
- 1mo ago First seen · 37 lines · 61 tokens per session scan A 66fb24a8b170
intent-driven-development is a command published in the GitHub repository naimkatiman/continuous-improvement (9 stars, last pushed 1mo ago), licensed MIT. It adds 61 tokens to every session and 494 once invoked, about $0.0002 per session on Opus 5.5. 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 commands, from other repositories
ap-swarm
Run a MultiAgentRuntime swarm in file mode — local journal at .runtime/conversation.md, no network.
reflect-promote
Promote learnings from skills to global CLAUDE.md.
reflect-meta
Show meta-learning statistics and pattern performance.
reflect-stats
Show cross-skill learning statistics.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.