clarify-intent-and-establish-shared-understanding skill
A skill that cross-examines a plan before work starts: numbered questions in rounds with a recommended answer and no changes until you confirm
- 205 ★ on the repository
- Last commit
- Apache-2.0
Extended access
Why this level
- The skill lets the agent use any available tools, search and subagents to verify facts, so during rounds it may read project files and reach the network
inference1/clarify-intent-and-establish-shared-understanding
Install
- Works in
In your terminal, with SkillFoxx CLI
npx skillfoxx add skills/clarify-intent-and-establish-shared-understandingDetects the agents on your machine, shows the access level and pins the version.
Other ways to install
Access and checks
How we reviewExtended accessThe tool runs code or makes network calls and only reads external data.
- The skill lets the agent use any available tools, search and subagents to verify facts, so during rounds it may read project files and reach the network
This is third-party code. Review the repository files before installing.
What it does
The skill turns a vague request into a shared understanding of the task before the agent does anything. It builds an implicit decision tree and walks it in rounds: in each round the agent asks every question whose prerequisites are already known, numbers them and attaches a recommended answer to each. Questions that depend on still-unresolved ones move to the next round. Facts that can be taken from the project directory, files, repository and connected tools the agent checks itself. People keep judgments, priorities, acceptable losses and missing information. Along the way the skill restates the shared understanding, separates confirmed facts, assumptions, interpretations and open decisions, looks for contradictions and revisits earlier conclusions when new answers change the picture. Until you explicitly confirm the shared understanding, the agent does not execute, publish or finalize anything consequential. That requires resolved dependencies, measurable success criteria and accepted key assumptions.
Who it is for. People who give an agent costly or irreversible tasks, such as research, a migration or an architecture decision, and want to test their plan for gaps first.
Good fit when
- Before a big research or migration you want the agent to cross-examine the plan: just write "grill me" or "pre-mortem"
- A request hides assumptions and the result may diverge from expectations: round questions bring them to the surface
- A strategy or proposal needs criticism before it is accepted: the skill triggers on red-team review and decision audit requests
- Requirements contradict each other: the skill looks for such spots and returns to accepted decisions if answers change the picture
- You need a written summary of what was agreed before starting: the skill periodically consolidates the shared understanding and asks for confirmation
Not a fit when
- The task is small and obvious: rounds of questions slow the work down, and the skill itself calls for a balance of rigor and speed
- The agent must start coding at once: the skill executes nothing until you confirm
- You need strictly one question at a time: this skill asks all independent questions in a round
- The session runs automatically without a person: the skill waits for answers and explicit confirmation
Example request
Grill my plan to migrate from MongoDB to Postgres: ask questions in rounds and change nothing until I confirm the shared understandingLimitations
- The README and SKILL.md disagree: the README promises one question at a time, while SKILL.md describes rounds of several questions. The SKILL.md behavior is what runs.
- The skill fires only on an explicit request for rigorous scrutiny («grill», «pressure-test», «red-team», «pre-mortem», «decision audit») and does not turn on for ordinary requests.
- The repository holds only an English instruction: no scripts, templates or sample answers.
- The skill lets the agent use any available tools and search to verify facts, so set network limits in the agent's settings.
How to disable. Delete the skill folder from `.claude/skills/` (or `~/.claude/skills/` for a global install), or manage removal through the `npx skills` utility following its instructions.
FAQ
How do I install the skill in Claude Code?
Run `npx skills add Inference1/clarify-intent-and-establish-shared-understanding -a claude-code`. Add `-g` to install for all projects, and the `--all` flag installs it for every supported agent.
How do I trigger the skill in a conversation?
Ask directly: "grill this plan", "do a pre-mortem", "run a red-team review". You can also call it with `/clarify-intent-and-establish-shared-understanding`. It does not respond to ordinary requests.
What does the agent do while questions are open?
It checks available facts and drives the questions but does not edit files, send or publish anything. It may continue after you confirm the shared understanding.
Do I have to accept the recommended answer?
No. Each question comes with a recommendation, but the decision stays with you: agree with the option or give your own.
How do I install the skill without npx?
Clone the repository and copy the folder so `SKILL.md` stays inside it: into the project's `.claude/skills/` or into `~/.claude/skills/`. For Codex and Cursor the project directory is `.agents/skills/`.
Discussion
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README in short
The page begins with three install paths: asking the agent, `npx skills add` with options for one agent or all, and manual copying with a table of Claude Code, Codex, Cursor, GitHub Copilot and Gemini CLI directories. An introduction follows on the dilemma between autonomy and interaction and the value of clarifying first, then a description of when the skill triggers and the rationale for its use.
README badge
Original SKILL.md
--- name: clarify-intent-and-establish-shared-understanding description: Whether you're thinking or getting things done, be clear, specific, and methodical. Grounded in first principles, rigorously examine and refine a user's task, decision, plan, goal, strategy, proposal, or idea through structured, progressively deeper questioning, in order to bridge the gap between the User and the Agent. Use when the user explicitly requests grilling, challenge, pressure-testing, cross-examination, red-team review, pre-mortem analysis, or a decision audit. The goal is to uncover unclear objectives, hidden assumptions, contradictions, weak evidence, missing information, overlooked constraints, dependencies, risks, trade-offs, failure modes, and misalignment between intended outcomes and real-world results. Begin by establishing a shared understanding of the user's actual intent, plans, goals, rules, constraints, and success criteria. Ask focused, high-leverage questions rather than broad or repetitive ones. Adapt each question based on previous answers, probing deeper where uncertainty, unsupported assumptions, or strategic weaknesses remain. Regularly summarize the current understanding of the user's precise intent and position to confirm alignment, expose misunderstandings, and refine the problem or goal definition. Distinguish facts, assumptions, hypotheses, and unknowns. Challenge reasoning rigorously while remaining constructive, respectful, and solution-oriented. Continue until the reasoning is internally coherent, evidence-aware, constraint-conscious, risk-assessed, and translated into a clearer, more actionable goal, decision, or plan. Ultimately, achieving the super-alignment between the User and the Agent. --- **Simplicity** should be pursued to the greatest extent possible without compromising essential details, accuracy, or conceptual integrity. **Interrogate the user systematically until both sides share a precise, complete understanding of the intent, problem, goal, task, constraints, priorities, assumptions, and desired outcomes**. 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. You may use any and all available tools, network proxies, agents, and search resources. Do not ask for information that can be reliably obtained from available context, current working directory, 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.