--- name: call-leading-question-guard description: Offline heuristic CALL-E phone call transcript skill that classifies agent questions into leading forms (tag questions, negative interrogatives, presupposition triggers, coercive framing), flags values affirmed under leading forms as tainted elicitation, and emits a neutral-elicitation goal template. It is not proof an answer was coerced, intent detection, or authorization to act automatically. license: MIT --- # call-leading-question-guard > **A leading question does not ask - it instructs the answer, then > collects a signature.** How a question is worded shapes what comes back. "What day works best for you?" and "You can pick up on Friday, right?" are both questions, but only one hands the person a decision; the other hands them a form to sign. On a phone call, where answers are spoken and immediately acted on, that wording pressure can end up driving bookings and record updates. This skill grades the agent's interrogation wording, not the callee's answers. ## When To Use - after any CALL-E call where the agent elicits decisions (dates, times, amounts, plan choices) from the person - when a recorded value was affirmed immediately after an agent question and you want to know how the question was framed - before placing calls, to craft a neutral-elicitation goal that opens open-form and confirms in bounded closed form - as a review aid alongside sibling conduct skills on the same transcript ## When Not To Use - on the callee's questions - only agent turns are scanned - to prove coercion; a flagged form is not proof the answer was coerced, and a confident person may genuinely agree - the card routes to review, always - during a call; strictly post-call analysis plus pre-call goal crafting - non-English transcripts; the form families are English lexical patterns ## Workflow ### Audit a finished call ```bash python3 scripts/leading_question_guard.py analyze \ --transcript path/to/call-result.json ``` Reads the real `get_call_run` result shape (`{status, result: {transcript}}`) or the flat fixture shape used by sibling skill fixtures; no goal file is needed. Emits a card: - `questions[]`: every agent question sentence, classified as `TAG` / `NEGATIVE_INTERROGATIVE` / `PRESUPPOSITION` / `COERCIVE` (leading) or `OPEN` / `CLOSED` (neutral) - `tainted_elicitation[]`: values the callee affirmed (affirmation word plus a weekday, ordinal date, amount, or clock time in the same turn) within two turns of a leading question - candidates for neutral re-confirmation, never auto-invalidations - `verdict`: `NEUTRAL_ELICITATION` / `LEADING_QUESTIONS_DETECTED` / `LEADING_TAINTED` / `NO_QUESTIONS_ASKED`, plus `unclear` paths (empty transcript, no agent turns) ### Craft the neutral goal ```bash python3 scripts/leading_question_guard.py craft --scenario neutral-elicitation ``` Emits the plan_call inputs JSON whose goal opens with an open question, lets the person answer in their own words, confirms in bounded closed form, and never re-asks a declined question in leading form. ## Scientific Foundation | Research | Relevance | |---|---| | Reconstruction of automobile destruction: An example of the interaction between language and memory (Loftus & Palmer, Journal of Verbal Learning and Verbal Behavior 13(5):585-589, 1974, doi 10.1016/S0022-5371(74)80011-3) | Foundational demonstration that question wording changes elicited answers - our question-form families operationalize wording pressure for calls | | The yes-no bias of large language models reflects answer order and wording, not shifts in moral judgment (Huang, arXiv 2607.05552, 2026) | Question wording and answer-order effects measured on LLM respondents - wording pressure is real even against machine interlocutors | Citation notes recorded during verification: both citations above were web-verified on 2026-10-01 with the exact journal/DOI and arXiv IDs as listed. This skill compares lexical question forms only, has no access to intent or tone, and labels every output `analysis_mode: "heuristic"`. ## Differences from sibling skills - `call-sycophancy-guard` catches the agent folding under the person's pushback; this skill catches the agent structuring questions to manufacture agreement in the first place. - `call-agent-certainty-calibrator` grades assertion wording; this skill grades interrogation wording. - `call-review` checks result-field support and compliance; question FORM is out of its scope.