intent-discovery

A guided process for clarifying a requested software change before implementation. It can turn the request into a user story, which describes who needs something, what they need, and why, with requirements and acceptance checks.

In plain words
What is it for?
Use it to define features, user stories, implementation plans, requirements, acceptance criteria, dependencies, and architecture or security considerations.
Why use it?
It reduces unclear scope and makes it easier to tell when a change is complete. The plan can be updated as decisions and constraints become clearer.

Skill for Claude CodeCodexCursor

Install

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.

agentmods
npx agentmods add skills/usrrname/cursorrules/intent-discovery
Any agent
npx skills add usrrname/cursorrules --skill intent-discovery
Clone the repo
git clone --depth 1 https://github.com/usrrname/cursorrules

Made for: Claude Code, Codex, Cursor.

Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 390 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00051 $0.00390
Opus 5 $0.00026 $0.00195
Sonnet 5 $0.00010 $0.00078
Haiku 4.5 $0.00005 $0.00039

Measured 2d ago against content hash 33315fbc23b8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

intent-discovery 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 2d 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.

.cursor/skills/intent-discovery/SKILL.md · 52 lines

What it actually says

Intent Discovery Workflow

This workflow uncovers user intent to craft plans for changes or features based on intent and outcomes.

Critical Rules

User Story Format

If a user story is created, it should follow the standard format: "As a [role], I want [goal] so that [benefit]"

  • Stories MUST be independent, negotiable, valuable, estimable, small, and testable
  • Every story MUST have clear requirements and acceptance criteria. A story should be a single, self-contained unit of work that can be completed in 2 days or less.
  • If a story or plan is created, it should be saved in .cursor/plans/ with the format <plan-title>.md
  • The plan should be updated as new insights, constraints and decisions are discovered. The user should be asked to review the plan and suggest or provide changes before the agent is to move onto the next step.

User Story Template

# User Story: [Title]

## Story
As a [role],
I want [goal/feature]
so that [benefit/value]

## Background

[Context and additional information]

## Acceptance Criteria
- [ ] Given [context], when [action], then [result]

## Technical Notes
- Dependencies:
- Architecture considerations:
- Security implications:
- Unknowns

## Related
- Architecture Decision Records: [links]
- Technical Documentation: [links]
- Dependencies: [story links] or Jira links

Checkpoint: the user is asked to review the document progress so far, suggest or provide changes before the agent is to move onto the next step.


## Examples
Changes

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.

  1. 2d ago First seen · 52 lines · 51 tokens per session scan A 33315fbc23b8

Subscribe to this mod's changes

intent-discovery is a skill published in the GitHub repository usrrname/cursorrules (10 stars, last pushed 4mo ago), licensed ISC. It adds 51 tokens to every session and 390 once invoked, about $0.0003 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.