run-rq

run-rq is a skill for Claude Code, Codex from marcoemrich/agentic_coding_lab. It costs 100 tokens per session (6,672 once invoked), scanned C, original, MIT.

An end-to-end workflow for advancing one research question (RQ) in a research repository. It checks the question setup, runs a batch process, monitors it, combines the results, and suggests updates to the findings.

In plain words
What is it for?
Use it to run a named research question, start and monitor its Docker batch, aggregate the results, and prepare possible findings changes.
Why use it?
It removes the need to coordinate several separate research steps by hand. It also checks the question's documentation before starting the run.

Skill for Claude CodeCodex

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 skills/marcoemrich/agentic_coding_lab/run-rq
Any agent
npx skills add marcoemrich/agentic_coding_lab --skill run-rq
Clone the repo
git clone --depth 1 https://github.com/marcoemrich/agentic_coding_lab

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 run-rq

README.md
[![agentmods](https://agentmods.dev/badge/skills/marcoemrich/agentic_coding_lab/run-rq.svg)](https://agentmods.dev/skills/marcoemrich/agentic_coding_lab/run-rq)
Your own site
<a href="https://agentmods.dev/skills/marcoemrich/agentic_coding_lab/run-rq"><img src="https://agentmods.dev/badge/skills/marcoemrich/agentic_coding_lab/run-rq.svg" alt="Measured on agentmods" height="20"></a>
Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,672 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. 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 $0.00100 $0.06672
Opus 5 $0.00050 $0.03336
Sonnet 5 $0.00020 $0.01334
Haiku 4.5 $0.00010 $0.00667

Measured 5d ago against content hash fe4e648fa44f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

run-rq scanned grade C with 1 finding 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 5d 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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

4. **Mid-execution cleanup after stop**: the youngest run dir in `experiments/runs/` that lacks `analysis-report.md` OR `transcript.jsonl` was interrupted mid-execution. Ask the user: "Delete interrupted run dir `<run-di
.claude/skills/run-rq/SKILL.md · 282 lines

How it starts

The opening of the file, as written. The whole thing — 282 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: run-rq

End-to-end orchestration for advancing a single research question (RQ) in this lab repo. Pure orchestration — every operation calls existing repo scripts; no new Python or Bash code is written.

Argument

  • RQ-N (e.g. RQ-model-quality) or a direct path to an RQ dir.
  • If not given: infer from the last user turn, otherwise ask back ("Which RQ? e.g. RQ-model-quality").

Repo conventions (from the top-level README.md and memory)

  • RQ dirs live in four subtrees: research/questions-claude/<chapter>-*/ (Claude-Code RQs), research/questions-opencode/<chapter>-*/ (OpenCode RQs), research/questions-cross/<chapter>-*/ (harness-übergreifende RQs), and research/workflow-dev/<chapter>-*/ (workflow evolution). The <chapter> prefix (e.g. 2.6) is an ordering label, not an id — the stable identity is the frontmatter id: (e.g. RQ-lean). Each RQ dir holds README.md, findings.md, runs.csv, summary.md.
  • Resolving an RQ-<slug> id to a path (the dir name carries a chapter number, not the id): grep all subtrees for the frontmatter id:. Anchor with ^id: and a trailing boundary so the whole slug must match exactly (no slug is a prefix of another, so an exact-line match is unambiguous):
    RQ_DIR=$(grep -rlE "^id:[[:space:]]*RQ-model-quality[[:space:]]*$" \
               research/questions-claude/*/README.md \
               research/questions-opencode/*/README.md \
               research/questions-cross/*/README.md \
               research/workflow-dev/*/README.md \
             2>/dev/null | head -1 | xargs -r dirname)
    
    On no match → ask the user. On multiple → take the first and inform the user. Pass "$RQ_DIR" to all scripts below (they accept any path and write outputs to the dir).
  • Mandatory frontmatter fields: id, question, factors, controls, outcomes, min_replicates, status.
  • Methodology constraint: v1/v2 only with prompt: prose; v3/v4/v5 with all three styles. If factors.workflow_x_prompt exists, no additional factors.workflow / controls.workflow is allowed.
  • Active katas: claim-office, game-of-life, sphinx-score, game-of-life-cli, claim-office-lite, mars-rover. controls.kata_base must be from this set. Each has the three prompt variants (-prose, -user-story, -example-mapping); all but mars-rover also have a <basename>-verification/ suite, so verification_pct is available there.
    • The list is not a ranking, but the pool is lopsided in practice: claim-office and game-of-life carry the bulk of the runs, sphinx-score is the established small quality kata, and mars-rover is near-unused. Prefer a kata that already has runs in neighbouring RQs — a fill on a fresh kata has no reference cells to compare against.
    • Check the actual kata dir before rejecting an RQ on this list. The list is hand-maintained and has lagged behind the repo before (sphinx-score was in use in three RQs while still missing here). ls experiments/katas/ is the authority; this line is a convenience copy.
  • Model IDs are lab-variant IDs (opus-4-7, opus-4-7-no-thinking, opus-4-6-portkey, opus-4-6-portkey-no-thinking, sonnet-4-6, sonnet-4-6-no-thinking, sonnet-4-6-portkey, sonnet-4-6-portkey-no-thinking, haiku-4-5, haiku-4-5-no-thinking, haiku-4-5-portkey, haiku-4-5-portkey-no-thinking). The -portkey suffix marks models routed via the Portkey gateway.
  • Aggregation is query-based: ALL runs in experiments/runs/ matching the selector query count — regardless of which batch produced them.
  • Batch plan is idempotent: counts existing matches and only fills missing replicates up to min_replicates.

Read the full file on GitHub · 282 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. 5d ago First seen · 282 lines · 100 tokens per session scan C fe4e648fa44f

Subscribe to this mod's changes

run-rq is a skill published in the GitHub repository marcoemrich/agentic_coding_lab (11 stars, last pushed yesterday), licensed MIT. It adds 100 tokens to every session and 6,672 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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