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.
npx skills add synaptiai/agent-capability-standard --skill inquiregit clone --depth 1 https://github.com/synaptiai/agent-capability-standardWrote 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.
[](https://agentmods.dev/skills/synaptiai/agent-capability-standard/inquire)<a href="https://agentmods.dev/skills/synaptiai/agent-capability-standard/inquire"><img src="https://agentmods.dev/badge/skills/synaptiai/agent-capability-standard/inquire.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00028 | $0.01897 |
| Opus 5 | $0.00014 | $0.00949 |
| Sonnet 5 | $0.00006 | $0.00379 |
| Haiku 4.5 | $0.00003 | $0.00190 |
Grade A, and why
inquire 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Intent
Generate targeted clarifying questions when a user request is ambiguous or underspecified, enabling the agent to gather missing information before committing to an action.
Success criteria:
- Questions target specific missing parameters or ambiguous interpretations
- Each question provides bounded answer options when applicable
- Confidence score reflects actual ambiguity level
- Evidence anchors reference the specific ambiguous elements
Compatible schemas:
schemas/output_schema.yamlreference/capability_ontology.yaml#/inquire
Inputs
| Parameter | Required | Type | Description |
|---|---|---|---|
ambiguous_input |
Yes | string|object | The underspecified request or goal to clarify |
context |
No | object | Previous conversation or domain context for better question generation |
max_questions |
No | integer | Maximum clarifying questions to generate (default: 3) |
Procedure
-
Analyze the input: Examine the ambiguous_input for completeness
- Identify required parameters for the likely intended action
- Check for conflicting interpretations
- Note any implicit assumptions that need validation
-
Categorize ambiguity types: Classify what's unclear
- Missing parameters: Required information not provided
- Conflicting interpretations: Multiple valid ways to interpret the request
- Constraint gaps: Boundaries or limits not specified
- Domain uncertainty: Unclear which domain or scope applies
-
Generate clarifying questions: For each ambiguity, formulate a question
- Target specific missing information
- Provide bounded options when possible (2-4 choices)
- Frame questions to elicit actionable answers
- Prioritize questions by impact on execution
-
Ground claims: Attach evidence anchors to the ambiguity analysis
- Reference specific phrases or words that are ambiguous
- Link to context that informed the interpretation
- Format:
input:phrase,context:field, orinference:reason
What ships with it
6 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.
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.
- 6d ago First seen · 222 lines · 28 tokens per session scan A b0ec894574e1
inquire is a skill published in the GitHub repository synaptiai/agent-capability-standard (4 stars, last pushed 7d ago), licensed Apache-2.0. It adds 28 tokens to every session and 1,897 once invoked, about $0.0001 per session on Opus 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 2026-08-31.
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