K-Ops: Command for Claude Code

.claude/commands/research_collect.md

research_collect is a command for Claude Code from arnaudgelas/K-Ops. It costs 2 tokens per session (1,065 once invoked), scanned A, original, MIT.

A research agent that gathers original sources for an active research project and turns them into a findings file. Original sources include official documentation, specifications, research papers, and code.

In plain words
What is it for?
It helps read the research brief and progress files, search for authoritative sources, create source summaries, and update the project’s findings.
Why use it?
It gives a research run a repeatable way to collect evidence and record where each claim comes from, while avoiding weaker commentary when better sources exist.

Command for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

This is arnaudgelas/K-Ops's own configuration. It tells Claude Code how to work on K-Ops itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything K-Ops configures →

Reuse

Borrowing it

Nothing to install: this file belongs to arnaudgelas/K-Ops. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/arnaudgelas/K-Ops/main/.claude/commands/research_collect.md
Clone the repo
git clone --depth 1 https://github.com/arnaudgelas/K-Ops

Made for: Claude Code.

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_collect

README.md
[![agentmods](https://agentmods.dev/badge/commands/arnaudgelas/k-ops/research_collect.svg)](https://agentmods.dev/commands/arnaudgelas/k-ops/research_collect)
Your own site
<a href="https://agentmods.dev/commands/arnaudgelas/k-ops/research_collect"><img src="https://agentmods.dev/badge/commands/arnaudgelas/k-ops/research_collect.svg" alt="Measured on agentmods" height="20"></a>
Per session 2 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,065 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.
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 $0.00002 $0.01065
Opus 5 $0.00001 $0.00532
Sonnet 5 $0.00000 $0.00213
Haiku 4.5 $0.00000 $0.00106

Measured 7d ago against content hash 3d64984ff9a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

research_collect 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.

.claude/commands/research_collect.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Research Collect agent for this repository.

Goal:

  • Gather primary sources for the active research run and convert them into a strong findings file.

Inputs:

  • Research brief: research/briefs/-.md
  • Status file: research/notes/-status.md
  • Progress log: research/notes/-progress.md
  • Findings file: research/findings/-.md

Instructions:

  1. Read orientation files first: Read the brief, status, progress log, and any existing findings or source notes.
  2. Search strategy: Search broadly first, then narrow to authoritative primary sources. Avoid citing commentary when primary documentation, official specs, or code is available.
  3. Write/Update Source Summaries:
    • For any new source, write a summary in notes/Sources/src-<id>.md using the canonical schema below.
    • For existing sources, update the file instead of creating duplicates.
    • Use canonical source_kind values: arxiv-paper | paper-pdf | github-repo-snapshot | github-file | official-doc | spec | blog | news | local-file | imported-model-report | citation-stub.
    • Use canonical evidence_strength values: primary-doc | official-spec | strong | code | maintainer-commentary | changelog | pr-issue | secondary | model-generated | stub | citation-only | image-only.
    • Populate kind-specific required fields in frontmatter.
    • Ensure extraction_coverage is populated for PDF sources with strong/official-spec/primary-doc strength (default: 1.0).
    • For imported reports, ensure authority: lead_only, verification_state: needs_primary_sources, and evidence_strength is secondary.
    • For citation stubs, ensure canonical_url is set, authority: lead_only, verification_state: needs_fetch, and evidence_strength is stub.
    • Ensure the required sections ## Reliability notes and ## Candidate concepts are present.
  4. Populate Findings File:
    • Update research/findings/<topic-slug>-<date>.md. Preserve its frontmatter (type: research-findings, topic_slug, etc.).
    • Populate ## Key Claims with atomic findings, citing the corresponding source summaries with inline wikilinks ([[Sources/src-<id>|src-<id>]]).
    • Populate ## Evidence with links to the source summaries, explaining what each contributes.
    • Populate ## Open Questions with gaps, contradictions, or unresolved questions.
  5. Progress Log: Append a short progress update when done.

Reference: Source Summary Schema

---
title: "<Descriptive title of the source>"
type: source-summary
source_id: src-<10-character-hex-id>
source_url: "<source url or file path>"
source_kind: <canonical_source_kind>
evidence_strength: <evidence_strength>
source_status: active
ingested_at: <ISO-8601 date, e.g. 2026-06-14T10:53:44Z>
tags:
  - kb/source
# --- Add kind-specific required fields below if applicable ---
# For arxiv-paper: authors, arxiv_id, published_date, abstract
# For paper-pdf: page_count
# For github-repo-snapshot: git_commit, branch, tracked_file_count, sampled_file_count
# For github-file: github_url, git_commit
# For official-doc: organization
# For spec: organization, version, status
# --- Add extraction_coverage if PDF (mandatory for strong/official-spec/primary-doc PDF sources) ---
# extraction_coverage: 1.0
---

## Summary

<2-4 sentence digest of what this source says and why it matters.>

## What this source is

<Detailed breakdown of the source, methodology, context, and focus areas.>

## Key claims

- <Atomic finding 1>
- <Atomic finding 2>

## Important evidence / details

- <Evidence detail with source-local anchors if available, e.g. page=12, line_start=20, line_end=35, path=src/utils.py>

## Candidate concepts

- <Concept candidates to promote>

## Open questions

- <Gaps, contradictions, or unresolved questions raised by this source>

## Reliability notes

<What this source does not cover, its methodology weaknesses, or why it might be wrong.>

## Related Concepts

- <Obsidian wikilinks to concepts, e.g., [[Concepts/ConceptName|ConceptName]]>

## Backlinks

- <Traceability backlinks>

Read the full file on GitHub · 108 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. 7d ago First seen · 108 lines · 2 tokens per session scan A 3d64984ff9a6

Subscribe to this mod's changes

research_collect is a command published in the GitHub repository arnaudgelas/K-Ops (1 stars, last pushed 19d ago), licensed MIT. It adds 2 tokens to every session and 1,065 once invoked, about $0.0000 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.