domain-discovery

domain-discovery is a skill for Claude Code, Codex from TanStack/intent. It costs 38 tokens per session (4,650 once invoked), scanned A, original, MIT.

A discovery process for turning a library’s documentation, source code, and maintainer knowledge into task-focused skills for AI coding agents.

In plain words
What is it for?
Use it when creating skills for a new library, reorganizing existing documentation, or deciding how a maintainer’s knowledge should be structured.
Why use it?
It helps uncover important details and failure cases that documentation may leave implicit, then organizes them around real developer tasks.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions AGENTS.md.

Good fit Use it when creating skills for a new library, reorganizing existing documentation, or deciding how a maintainer’s knowledge should be structured.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tanstack/intent/domain-discovery
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.

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

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for domain-discovery

README.md
[![agentmods](https://agentmods.dev/badge/skills/tanstack/intent/domain-discovery/github.svg)](https://agentmods.dev/skills/tanstack/intent/domain-discovery)
Your own site
<a href="https://agentmods.dev/skills/tanstack/intent/domain-discovery"><img src="https://agentmods.dev/badge/skills/tanstack/intent/domain-discovery/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.

agentmods 80×15 button for domain-discovery

Your own site · 80×15
<a href="https://agentmods.dev/skills/tanstack/intent/domain-discovery"><img src="https://agentmods.dev/badge/skills/tanstack/intent/domain-discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,650 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 10 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Prompt Injection · line 414
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 424
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 426
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 428
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 429
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 430
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 431
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 433
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 439
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 435
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
How audits are shown
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 5.1 $0.00038 $0.04650
Opus 5.5 $0.00015 $0.01860
Sonnet 5.5 $0.00008 $0.00930
Haiku 4.5 $0.00004 $0.00465

Measured 1mo ago against content hash 84c9de6d9678, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

domain-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 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.

packages/intent/meta/domain-discovery/SKILL.md · 296 lines

How it starts

The opening of the file, as written. The whole thing — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Domain Discovery & Maintainer Interview

You are extracting domain knowledge for a library to produce a structured domain map. Your job is not to summarize documentation — it is to build a deep understanding of the library first, then use that understanding to surface the implicit knowledge that maintainers carry but docs miss.

The output is a set of task-focused skills — each one matching a specific developer moment ("implement a proxy", "set up auth", "audit before launch"). Domains are an intermediate conceptual grouping you use during analysis; the final skills emerge from the intersection of domains and developer tasks.

There are five phases. Always run them in order — unless the lightweight path applies (see below).

  1. Quick scan — orient yourself (autonomous)
  2. High-level interview — extract the maintainer's task map
  3. Deep read — fill in failure modes and detail (autonomous)
  4. Detail interview — gap-targeted questions, AI-agent failures
  5. Finalize artifacts

Lightweight path (small libraries)

After Phase 1, decide whether the library warrants the full five-phase flow or the compressed flow below. This is a judgment call — lean toward full discovery unless the library is obviously small (single-purpose utility, 2–3 distinct developer tasks max). Use a compressed flow when the skill surface is small enough that two interview rounds would be redundant:

  1. Phase 1 — Quick scan (same as full flow)
  2. Phase 2+4 combined — Single interview round. Combine the high-level task map questions (Phase 2) with gap-targeted and AI-agent-specific questions (Phase 4) into one interview session of 4–8 questions total. Skip the draft-review step since the skill set is small enough to confirm in one pass.
  3. Phase 3 — Deep read (same as full flow, but scope is smaller)
  4. Phase 5 — Finalize artifacts (same as full flow)

The lightweight path produces identical output artifacts (domain_map.yaml and skill_spec.md). It just avoids two separate interview rounds when the library is small enough that one round covers everything.

Read the full file on GitHub · 296 lines

Files

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.

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. 1mo ago Changed · -168 lines · -43 tokens per session 84c9de6d9678
  2. 1mo ago Changed · -474 lines · -2 tokens per session a5c9d7965d6c
  3. 1mo ago First seen · 938 lines · 83 tokens per session scan A bc49f900b0a0

Subscribe to this mod's changes

domain-discovery is a skill published in the GitHub repository TanStack/intent (355 stars, last pushed 7d ago), licensed MIT. It adds 38 tokens to every session and 4,650 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 2026-08-30.

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