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 thuong-nc/perlytics-skill --skill clarify-questiongit clone --depth 1 https://github.com/thuong-nc/perlytics-skillWrote 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/thuong-nc/perlytics-skill/clarify-question)<a href="https://agentmods.dev/skills/thuong-nc/perlytics-skill/clarify-question"><img src="https://agentmods.dev/badge/skills/thuong-nc/perlytics-skill/clarify-question.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 | $0.00056 | $0.00847 |
| Opus 5 | $0.00028 | $0.00424 |
| Sonnet 5 | $0.00011 | $0.00169 |
| Haiku 4.5 | $0.00006 | $0.00085 |
Grade A, and why
clarify-question 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 7d 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clarify Question
Purpose
Turn a vague business or analytics question into a clear analysis brief before answering.
When to use
Use this skill when:
- the user asks "why", "what happened", or "how is X doing" without enough detail
- the user asks to analyze a file, CSV, spreadsheet, report, dashboard, or table without specifying the metric or decision
- the user says "analyze this data," "read these numbers," or "find insights" but the analytical frame is still missing
- the metric is implied but not defined
- the comparison period is missing
- the requested answer could change depending on entity, segment, or grain
When not to use
Do not use this skill when:
- the question is already tightly scoped and fully specified
- the user is asking for a mechanical task rather than analysis framing
- the necessary metric, baseline, and decision context are already explicit
Required thinking discipline
- Do not answer the business question immediately.
- Separate clarification from explanation.
- Ask only the minimum questions needed to make the request answerable.
- If context remains missing, state assumptions explicitly before continuing.
- Evidence constraint: Every conclusion must cite specific data — a number, a rate, a segment, or a timeframe. Do not speculate without evidential basis. If data is insufficient, state what is missing rather than asserting an unsupported inference.
Workflow
- Restate the user's question in neutral business terms.
- Identify missing elements:
- Metric: the quantitative definition being analyzed
- Dimension: the categorical breakdown used to slice the metric
- Grain: the unit of observation (day, order, user, account, etc.)
- Timeframe: the period included in the analysis
- Baseline: the reference point used for comparison
- Filter: the inclusion or exclusion rule that narrows scope
- Decision context: what action or decision this analysis is meant to inform
- Ask the smallest useful set of clarifying questions.
- If the user cannot answer, propose default assumptions and mark them clearly.
- Produce a clarified analysis brief before any interpretation.
What ships with it
2 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.
- 7d ago First seen · 101 lines · 56 tokens per session scan A ff73e47afc47
clarify-question is a skill published in the GitHub repository thuong-nc/perlytics-skill (5 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 56 tokens to every session and 847 once invoked, about $0.0003 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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