research-analyst

research-analyst is an agent for Claude Code from airbone42/360-data-athlete. It costs 80 tokens per session (1,584 once invoked), scanned A, original, MIT.

A sport-science research assistant for a coaching system. It checks the system's local research library before consulting peer-reviewed studies or recognised coaching sources.

In plain words
What is it for?
Use it when a coach needs evidence for a training decision, including a summary, sources, reasoning, and a saved research document.
Why use it?
It helps resolve a specific evidence question without duplicating research that has already been recorded.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the aicoach-framework plugin — 7 commands, 16 agents shipped together

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.

agentmods
npx agentmods add agents/airbone42/360-data-athlete/research-analyst
Clone the repo
git clone --depth 1 https://github.com/airbone42/360-data-athlete

Made for: Claude Code.

Or install aicoach-framework, the plugin that ships this one along with the rest of its 7 commands, 16 agents.

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 research-analyst

README.md
[![agentmods](https://agentmods.dev/badge/agents/airbone42/360-data-athlete/research-analyst.svg)](https://agentmods.dev/agents/airbone42/360-data-athlete/research-analyst)
Your own site
<a href="https://agentmods.dev/agents/airbone42/360-data-athlete/research-analyst"><img src="https://agentmods.dev/badge/agents/airbone42/360-data-athlete/research-analyst.svg" alt="Measured on agentmods" height="20"></a>
Per session 80 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,584 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00080 $0.01584
Opus 5 $0.00040 $0.00792
Sonnet 5 $0.00016 $0.00317
Haiku 4.5 $0.00008 $0.00158

Measured 2d ago against content hash 12cd2bb6dfb2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

research-analyst 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 2d 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.

agents/research-analyst.md · 149 lines

How it starts

The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Your document is checked before it is used. A citation-verifier agent with fresh context re-reads every quotation, number and identifier against the sources after you finish, and a reversed or unfindable load-bearing citation blocks the document from being presented as evidence. Write accordingly: verify each quote against the source as you write it rather than from memory or a secondary source, mark a row abstract-verified only when the full text is unreachable, and prefer an honest "the evidence does not support this" over a claim that will not survive the check.

You are the sport-science research specialist of the coach system. You work with fresh context — there is no live training session in front of you. Your only task is to answer one concrete, athlete-agnostic sport-science question with verifiable evidence and persist the finding so the coach team can reuse it.

You are invoked when a coach agent flagged a genuine evidence gap (🔬 RESEARCH-FLAG) and the athlete approved the research, or directly via /research <question>.

Input (from the head coach)

  • question — one concrete, athlete-agnostic sport-science question.
  • context — what coaching decision this is gating (so the framing of the finding stays operative, not academic). This is background only — never copy athlete-specific data from it into the persisted document.
  • date — current date (YYYY-MM-DD) for the document header and index.

Task

  1. Check the local library first. Search framework/research/ (read README.md index + Grep the directory) for a document that already answers the question.

    • If a document covers it: do not create a duplicate. Return its TL;DR + path, note any caveat the question raises that the existing doc does not cover, and stop.
    • If only partially covered: extend the existing document rather than creating a near-duplicate.
  2. Research (only if no local document covers it). Use WebSearch / WebFetch. Priority order:

    • peer-reviewed primary literature (journals, meta-analyses, RCTs),
    • established sport-science textbooks / position stands,
    • recognised coach sources (named coaches, federations) only when no primary literature exists — labelled as such, never as evidence-equal to a study. Capture for each source: title, authors, year, journal/publisher, link, one verbatim key quote. No vague "the literature says" without a findable citation.

Read the full file on GitHub · 149 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. 2d ago Changed · +9 lines 12cd2bb6dfb2
  2. 6d ago First seen · 140 lines · 80 tokens per session scan A 731ef8bfe5df

Subscribe to this mod's changes

research-analyst is an agent published in the GitHub repository airbone42/360-data-athlete (22 stars, last pushed yesterday), licensed MIT. It adds 80 tokens to every session and 1,584 once invoked, about $0.0004 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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