finding-unknowns

finding-unknowns is a skill for Claude Code from baizhiyuan/finding-unknowns-skill. It costs 133 tokens per session (8,988 once invoked), scanned B, original, MIT.

A planning skill for uncovering information, assumptions, and preferences that are missing from an unclear software task. It uses activities such as brainstorming, interviews, prototypes, references, and review questions.

In plain words
What is it for?
It is for clarifying ambiguous projects, exploring possible approaches, planning long tasks, and checking whether the requirements are understood.
Why use it?
It helps reveal hidden requirements before they lead to the wrong design or implementation, especially in unfamiliar areas or high-stakes work.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: reads .claude/ paths; mentions subagents; names the AskUserQuestion tool.

Part of the finding-unknowns plugin — 1 skill, 4 commands, 4 agents shipped together

Good fit It is for clarifying ambiguous projects, exploring possible approaches, planning long tasks, and checking whether the requirements are understood.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/baizhiyuan/finding-unknowns-skill/finding-unknowns
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 baizhiyuan/finding-unknowns-skill --skill finding-unknowns
Clone the repo
git clone --depth 1 https://github.com/baizhiyuan/finding-unknowns-skill

Made for: Claude Code.

Or install finding-unknowns, the plugin that ships this one along with the rest of its 1 skill, 4 commands, 4 agents.

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 finding-unknowns

README.md
[![agentmods](https://agentmods.dev/badge/skills/baizhiyuan/finding-unknowns-skill/finding-unknowns/github.svg)](https://agentmods.dev/skills/baizhiyuan/finding-unknowns-skill/finding-unknowns)
Your own site
<a href="https://agentmods.dev/skills/baizhiyuan/finding-unknowns-skill/finding-unknowns"><img src="https://agentmods.dev/badge/skills/baizhiyuan/finding-unknowns-skill/finding-unknowns/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 finding-unknowns

Your own site · 80×15
<a href="https://agentmods.dev/skills/baizhiyuan/finding-unknowns-skill/finding-unknowns"><img src="https://agentmods.dev/badge/skills/baizhiyuan/finding-unknowns-skill/finding-unknowns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 133 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,988 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00133 $0.08988
Opus 5 $0.00067 $0.04494
Sonnet 5 $0.00027 $0.01798
Haiku 4.5 $0.00013 $0.00899

Measured 8d ago against content hash 85fb3e633fc4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade B, and why

finding-unknowns scanned grade B with 1 finding 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 8d 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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

`findingUnknowns.ambiguityThreshold` from `./.claude/settings.json` (project) then
skills/finding-unknowns/SKILL.md · 676 lines

How it starts

The opening of the file, as written. The whole thing — 676 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Finding Unknowns

Distilled from Thariq Shihipar's essay "A Field Guide to Fable: Finding Your Unknowns" (@trq212 — https://x.com/trq212/status/2073100352921215386). Community skill; not affiliated with or endorsed by Anthropic.

<Use_When>

  • The user is starting work in a new domain or an unfamiliar part of the codebase
  • The task involves taste — "I'll know it when I see it" criteria that resist specification
  • The task is long-horizon and a wrong early assumption would compound
  • A previous attempt came back wrong and the spec, not the execution, is the suspect
  • The user says "blindspot pass", "unknown unknowns", "interview me", "brainstorm directions", "quiz me", or "Cartographer mode" </Use_When>

<Do_Not_Use_When>

  • The request is specific and trivial (typo, one-liner, obvious bug fix) — execute directly
  • The user has a detailed spec with file paths and acceptance criteria — go build it
  • The user wants ontology/entity-convergence tracking or OMC-native state/pipeline machinery (autopilot/ralph/team handoff) — use oh-my-claudecode:deep-interview instead; Cartographer covers ambiguity gating and an approval-gated bridge without that runtime
  • The user explicitly says "just do it" — respect that; offer one sentence of risk if material, then proceed </Do_Not_Use_When>

<Why_This_Exists> Model capability is no longer the bottleneck on long-horizon work; clarity is. Generic requirements gathering asks "what do you want?" — but users cannot answer for the unknowns they are not aware of. This skill's premise is that different kinds of unknowing need different instruments: blind spots need reconnaissance, tacit taste needs reaction to prototypes, nameable gaps need targeted questions, and comprehension needs examination. A single uniform interview under-serves all four. </Why_This_Exists>

<Execution_Policy>

  • ALWAYS locate the unknown on the quadrant map (Phase 0) before choosing a technique
  • Establish the user's starting point — where they are in their thinking, their experience with this problem and codebase. The same task needs different probing for an expert than for a first-timer
  • Discovery ends at understanding. No discovery technique slides into implementation
  • Never ask the user a question the territory can answer — explore the codebase first
  • Interview via AskUserQuestion (clickable options). Up to 3 independent questions per round, ordered by blast-radius/regret; never bundle dependent questions — where one answer would change the next question's framing, ask those one at a time
  • Architecture-changing unknowns outrank trivia, always
  • "You have no significant unknowns here" is a valid and valuable result — say it plainly rather than manufacturing concerns
  • Deviations get logged, not buried. Comprehension is the merge gate, not a green diff
  • Prefer single-file self-contained HTML artifacts for anything the user must react to or review (prototypes, plans, quiz reports); markdown fallback for pure-terminal flows
  • Delegate to companion agents when installed and the case is non-trivial; run inline otherwise. Every technique works standalone </Execution_Policy>

Read the full file on GitHub · 676 lines

Files

What ships with it

1 file 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. 8d ago First seen · 676 lines · 133 tokens per session scan B 85fb3e633fc4

Subscribe to this mod's changes

finding-unknowns is a skill published in the GitHub repository baizhiyuan/finding-unknowns-skill (5 stars, last pushed 2mo ago), licensed MIT. It adds 133 tokens to every session and 8,988 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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