data-analysis-quality-gate

data-analysis-quality-gate is a skill for Claude Code, Codex from byteseek/Mira. It costs 32 tokens per session (1,729 once invoked), scanned A, original, Apache-2.0.

A quality check for research conclusions that depend on numbers, such as growth rates, margins, market size, valuation, rankings, or time-series comparisons.

In plain words
What is it for?
Use it when quantitative evidence may affect a research thesis, recommendation, comparison, scenario, or other judgment, to decide what data and calculations are required.
Why use it?
It requires reproducible data and calculations, or clearly weakens conclusions when the needed evidence or computation is missing.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when quantitative evidence may affect a research thesis, recommendation, comparison, scenario, or other judgment, to decide what data and calculations are required.

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Install with agentmods
npx agentmods add skills/byteseek/mira/data-analysis-quality-gate
Install

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.

Any agent
npx skills add byteseek/Mira --skill data-analysis-quality-gate
Clone the repo
git clone --depth 1 https://github.com/byteseek/Mira

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for data-analysis-quality-gate

README.md
[![agentmods](https://agentmods.dev/badge/skills/byteseek/mira/data-analysis-quality-gate/github.svg)](https://agentmods.dev/skills/byteseek/mira/data-analysis-quality-gate)
Your own site
<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.

agentmods 80×15 button for data-analysis-quality-gate

Your own site · 80×15
<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>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,729 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 11d ago against content hash 9158a63c1bd2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

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.

skills/data-analysis-quality-gate/SKILL.md · 197 lines

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_impactresearch_actionactionability_bridge 或 durable conclusion 的数量判断

Inputs

  • research_object
  • research_question
  • market_scope
  • time_boundary
  • candidate_numeric_claims
  • available_sources
  • user_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_dependency none / low / medium / high
  • calculation_required yes / no
  • data_requirement_brief_required yes / no
  • calculation_ledger_required yes / no
  • tool_consent_required yes / no
  • allowed_without_tool yes / no
  • downgrade_if_not_calculated none / calculation_gap / source_gap / watch_only / needs_refresh
  • recommended_tool_path none / manual_formula_note / local_csv_script / spreadsheet / python / public_api / external_plugin
  • calculation_depth none / formula_note / ledger_required / full_model_required
  • refresh_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: nonelow
  • 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。

Read the full file on GitHub · 197 lines

Changes

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.

  1. 11d ago First seen · 197 lines · 32 tokens per session scan A 9158a63c1bd2

Subscribe to this mod's changes

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.

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