clarify-intent-and-establish-shared-understanding

clarify-intent-and-establish-shared-understanding is a skill for Codex from Inference1/clarify-intent-and-establish-shared-understanding. It costs 303 tokens per session (950 once invoked), scanned A, original, Apache-2.0.

A structured questioning method for making a plan, task, decision, or idea precise before acting on it. It examines goals, constraints, assumptions, priorities, and the desired result one round of questions at a time.

In plain words
What is it for?
Use it to pressure-test proposals, refine project plans, clarify decisions, define tasks, and establish a shared understanding with an agent.
Why use it?
It helps expose missing information, hidden assumptions, contradictions, and unclear choices before they cause rework.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to pressure-test proposals, refine project plans, clarify decisions, define tasks, and establish a shared understanding with an agent.

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Install with agentmods
npx agentmods add skills/inference1/clarify-intent-and-establish-shared-understanding/clarify-intent-and-establish-shared-understanding
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 Inference1/clarify-intent-and-establish-shared-understanding --skill clarify-intent-and-establish-shared-understanding
Clone the repo
git clone --depth 1 https://github.com/Inference1/clarify-intent-and-establish-shared-understanding

Made for: 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 clarify-intent-and-establish-shared-understanding

README.md
[![agentmods](https://agentmods.dev/badge/skills/inference1/clarify-intent-and-establish-shared-understanding/clarify-intent-and-establish-shared-understanding/github.svg)](https://agentmods.dev/skills/inference1/clarify-intent-and-establish-shared-understanding/clarify-intent-and-establish-shared-understanding)
Your own site
<a href="https://agentmods.dev/skills/inference1/clarify-intent-and-establish-shared-understanding/clarify-intent-and-establish-shared-understanding"><img src="https://agentmods.dev/badge/skills/inference1/clarify-intent-and-establish-shared-understanding/clarify-intent-and-establish-shared-understanding/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 clarify-intent-and-establish-shared-understanding

Your own site · 80×15
<a href="https://agentmods.dev/skills/inference1/clarify-intent-and-establish-shared-understanding/clarify-intent-and-establish-shared-understanding"><img src="https://agentmods.dev/badge/skills/inference1/clarify-intent-and-establish-shared-understanding/clarify-intent-and-establish-shared-understanding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 303 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 950 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.
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 $0.00303 $0.00950
Opus 5.5 $0.00121 $0.00380
Sonnet 5.5 $0.00061 $0.00190
Haiku 4.5 $0.00030 $0.00095

Measured today against content hash 627297f44b4a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

clarify-intent-and-establish-shared-understanding 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.

SKILL.md · 54 lines

What it actually says

Interrogate the user systematically until both sides share a precise, complete understanding of the intent, problem, goal, task, constraints, priorities, assumptions, and desired outcome.

Construct and navigate an implicit decision tree. Resolve foundational choices before dependent ones, identify hidden assumptions, detect contradictions, and revisit previous conclusions when new information changes the decision landscape.

Proceed through the decision tree iteratively, one round at a time. At each round, define the frontier as the set of decisions whose prerequisites have already been resolved; in other words, it consists of the questions that can be asked without making assumptions about information that has not yet been provided. Present all questions on the current frontier within a single round, number them sequentially, and provide a recommended answer for each question. Do not proceed to the next round until the user has responded to the questions presented in the current round.

Format a round like so:

❓ **Q1** - **<question title>**: <question body, might be multiple paragraphs, including multiple choices>

➡️ <your recommended answer>

---

❓ **Q2** - **<question title>**: <question body, might be multiple paragraphs, including multiple choices>

➡️ <your recommended answer>

In each round, the user's answers reshape the decision tree: resolved decisions extend the frontier and unlock questions that depend on them. Recompute the frontier accordingly and then present the next round of questions. Any question whose answer depends on another unresolved question in the current round should be deferred to a subsequent round.

Do not combine independent questions. Each question should:

  • target a specific unresolved decision or ambiguity;
  • briefly explain why the answer affects the outcome;
  • provide a clearly labeled recommended option when sufficient context exists;
  • preserve user agency by making clear that the final choice belongs to the user.

Do not ask for information that can be reliably obtained from available context, code repositories, files, tools, connected sources, or other authorized inputs. Retrieve or verify such information directly when possible. Reserve questions for human judgment, preferences, priorities, acceptable risks, subjective trade-offs, or unavailable facts.

Continuously restate and refine the emerging understanding. Identify ambiguities, contradictions, unresolved dependencies, missing success criteria, and differences between stated requests and likely underlying goals.

Continuously maintain a shared mental model by:

  • summarize the current understanding when meaningful progress is made;
  • separate confirmed facts, assumptions, interpretations, and open decisions;
  • highlight ambiguity, conflicting requirements, missing constraints, and unclear evaluation criteria;
  • check whether the inferred objective matches the user's actual intent.

Do not execute, implement, modify, submit, publish, or finalize any consequential output until:

  1. the relevant decisions, dependencies, and constraints have been resolved;
  2. the desired outcome and measurable success criteria are explicit;
  3. major assumptions and trade-offs have been surfaced and accepted;
  4. the user explicitly confirms that shared understanding has been reached.

Maintain a balance between rigor and efficiency. Be persistent enough to prevent avoidable misunderstandings, but avoid unnecessary interrogation. Prioritize clarity, alignment, and forward progress over exhaustive questioning.

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. today Changed · +17 tokens per session 627297f44b4a
  2. 1mo ago First seen · 54 lines · 286 tokens per session scan A 9392f9a5b2dc

Subscribe to this mod's changes

clarify-intent-and-establish-shared-understanding is a skill published in the GitHub repository Inference1/clarify-intent-and-establish-shared-understanding (206 stars, last pushed today), licensed Apache-2.0. It adds 303 tokens to every session and 950 once invoked, about $0.0012 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.