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 byteseek/Mira --skill data-analysis-quality-gategit clone --depth 1 https://github.com/byteseek/MiraWrote 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/byteseek/mira/data-analysis-quality-gate)<a href="https://agentmods.dev/skills/byteseek/mira/data-analysis-quality-gate"><img src="https://agentmods.dev/badge/skills/byteseek/mira/data-analysis-quality-gate/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.
<a href="https://agentmods.dev/skills/byteseek/mira/data-analysis-quality-gate"><img src="https://agentmods.dev/badge/skills/byteseek/mira/data-analysis-quality-gate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00032 | $0.01729 |
| Opus 5 | $0.00016 | $0.00864 |
| Sonnet 5 | $0.00006 | $0.00346 |
| Haiku 4.5 | $0.00003 | $0.00173 |
Grade A, and why
data-analysis-quality-gate 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 11d 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Analysis Quality Gate
这个 skill 用于在 Mira 研究中判断数量型结论是否需要可复算数据、工具计算或显式降级。
它不是一个独立数据分析插件,也不绑定 Data Analytics、Python、Spreadsheet 或外部 API。它的职责是把 LLM 从“直接给数字结论”约束为:
- 先提出数据需求
- 再判断是否必须计算
- 决定是否需要征求用户同意动用工具
- 记录公式、口径、来源和限制
- 对没有完成计算的数量型结论降级
Use When
当研究结论涉及以下任一内容时,必须进入本 gate,或明确写明 waived reason:
- 同比、环比、CAGR、run-rate、margin bridge
- peer comparison、peer ranking、相对估值、相对财务质量
- valuation implied expectation、base / bull / bear scenario math
- 市场规模、渗透率、份额、TAM / SAM / SOM
- 三表交叉校验、现金流质量、营运资本异常
- 宏观、商品、价格、库存、利率、就业或通胀时间序列
- 多来源数字冲突或口径不一致
- 任何会影响
thesis_impact、research_action、actionability_bridge或 durable conclusion 的数量判断
Inputs
research_objectresearch_questionmarket_scopetime_boundarycandidate_numeric_claimsavailable_sourcesuser_speed_preference可选。若用户明确要求快看,可降低计算深度,但不能升级结论强度。tool_constraints可选。说明是否允许本地脚本、CSV、Spreadsheet、联网、外部 API 或插件。
Gate Output
每次运行本 gate,至少输出:
quant_dependencynone/low/medium/highcalculation_requiredyes/nodata_requirement_brief_requiredyes/nocalculation_ledger_requiredyes/notool_consent_requiredyes/noallowed_without_toolyes/nodowngrade_if_not_calculatednone/calculation_gap/source_gap/watch_only/needs_refreshrecommended_tool_pathnone/manual_formula_note/local_csv_script/spreadsheet/python/public_api/external_plugincalculation_depthnone/formula_note/ledger_required/full_model_requiredrefresh_condition
Calculation Depth
none
用于没有派生数量结论,或数量只作为非核心背景且已有可靠来源直接披露的场景。
输出要求:
- 记录
quant_dependency: none或low - 不生成 calculation artifact
formula_note
用于简单、低行数、可口头复核的计算,例如一个同比、一个 run-rate sanity check、简单估值倍数或明确公式的市场隐含值。
输出要求:
- 在正文或 source note 写明公式、输入来源、期间和限制
- evidence log 可记录
claim_type=derived_calculation - 不默认生成
calculation-ledger.csv
ledger_required
用于会影响 thesis impact、research action、actionability bridge、peer ranking、scenario table 或多来源冲突处理的计算。
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.
- 11d ago First seen · 197 lines · 32 tokens per session scan A 9158a63c1bd2
data-analysis-quality-gate is a skill published in the GitHub repository byteseek/Mira (268 stars, last pushed 2d ago), licensed Apache-2.0. It adds 32 tokens to every session and 1,729 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
daemon
Continuous autonomous operation mode. Keeps campaigns running 24/7 by chaining Claude Code sessions via RemoteTrigger. Each session picks up from the campaign's continuation state, works until context runs low or the phase completes, then schedules the next session. Auto-stops on campaign completion or budget…
improve
Autonomous quality improvement loop. Scores a target against a rubric, selects the highest-leverage axis, attacks it, verifies, documents, and loops. No pre-planning between iterations — each loop re-scores from scratch.
setup
First-run experience for the harness. Three modes: Recommended (guided, 3 min), Full Tour (guided + skill walkthrough, 8 min), and Express (zero questions, 30 sec). Installs hooks first, detects stack, configures harness.json, runs a live demo on real code, and prints a reference card.
evolve
Research-driven multi-cycle improvement director. Forms causal hypotheses about why scores are low, validates them with scout agents before attacking, dispatches axis-parallel fleet attacks, extracts transferable patterns, and runs indefinitely within a budget envelope. Accumulates a persistent belief model and…
research
Focused research investigations. Converts questions into structured findings with confidence levels and source citations. Single agent by default; with --parallel (or when the question decomposes into 3+ independent angles) it spawns scout agents whose findings are compressed into a unified brief. Does not make…
watch
File sentinel that monitors the working directory for changes and marker comments, then auto-triggers appropriate skills. Poll-based via git diff against the last scan commit. Writes intake items for batch processing and routes marker actions through /do. Use for automatic reactions to file changes; do NOT use for…