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 agentmods add instructions/marcoemrich/agentic_coding_lab/claude-mdgit clone --depth 1 https://github.com/marcoemrich/agentic_coding_labWhat 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 | $0.03491 | $0.03491 |
| Opus 5 | $0.01746 | $0.01746 |
| Sonnet 5 | $0.00698 | $0.00698 |
| Haiku 4.5 | $0.00349 | $0.00349 |
Grade A, and why
agentic_coding_lab CLAUDE.md 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.
How it starts
The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Coding Lab
Research framework for studying how TDD workflow structures and prompt styles affect AI-generated code quality. Runs Claude Code CLI in Docker containers against coding katas, then analyzes results via RQ-driven aggregation.
Full documentation: README.md — methodology, RQ frontmatter schema, workflow descriptions, model configurations, script reference, metrics glossary.
Skills
/run-rq RQ-N
End-to-end RQ orchestration: validate README → generate fill plan → start Docker batch → monitor progress → aggregate → propose findings updates. Pure orchestration calling existing repo scripts.
- Triggers: "run-rq", "fill RQ-N", "RQ-N voranbringen", "Forschungsfrage N starten"
- Details:
.claude/skills/run-rq/SKILL.md
/reanalyze RQ-N
Re-run analysis pipeline on all runs matching an RQ, reaggregate metrics, and propose findings updates. No new runs — only refreshes existing data after pipeline changes.
- Triggers: "reanalyze RQ-N", "reanalyse", "Runs neu analysieren"
- Details:
.claude/skills/reanalyze/SKILL.md
/build-overview
Generates a frozen experiment-overview snapshot across all RQs under research/reports/. Runs generate-snapshot-skeleton.py, then fills synthesis sections from findings.md files.
- Details:
.claude/skills/build-overview/SKILL.md
/exact-coding-baseline-export [date] [source-workflow]
Mint a new exact-coding-baseline-YYYY-MM-DD/ snapshot under research/workflow-dev/export/. Auto-detects the current correctness-oriented source workflow from research/workflow-dev/workflow-construction.md (the "Default für korrekheits-kritische Arbeit" recommendation), or takes an explicit source name. Copies source files, applies the HITL transformation (Step-8 checkpoints, autonomy-level switch, mode-neutral execution rule), and writes README + VERSION inside .claude/. Templates (HITL consumable, README, tdd-execution-mode) live in the skill directory.
- Triggers: "exact-coding baseline export", "neue exact-coding baseline", "exact-coding-baseline-export"
- Details:
.claude/skills/exact-coding-baseline-export/SKILL.md
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.
- 2d ago First seen · 143 lines · 3,491 tokens per session scan A 7d79ee0c5ca3
agentic_coding_lab CLAUDE.md is an instructions file published in the GitHub repository marcoemrich/agentic_coding_lab (11 stars, last pushed 16d ago), licensed MIT. It adds 3,491 tokens to every session, about $0.0175 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 instructions, from other repositories
vscode_abap_remote_fs CLAUDE.md
Instructions for marcellourbani/vscode_abap_remote_fs, covering abap fs development guidelines, workflow and constraints.
sheal AGENTS.md
Instructions for liwala/sheal, covering agent instructions, agent operating policy, 1. tdd discipline — strict order, the only exception: spikes and 2. tests assert intent.
digital-service-orchestra skills.instructions.md
Instructions for navapbc/digital-service-orchestra, a project described as: Workflow infrastructure plugin for Claude Code projects — TDD-driven sprint management, review gates, hook parameterization, and multi-stack config.
spec-driven-tdd AGENTS.md
Instructions for strelov1/spec-driven-tdd: This repo is a skill-pack. When implementing an OpenSpec change, invoke the spec-driven-tdd skill and follow its lifecycle: plan in OpenSpec, isolate in a worktree, implement each task via TDD → simplify → review, then finish + archive.
mcp-repo-onboarding AGENTS.md
Instructions for rogermt/mcp-repo-onboarding, covering agents.md — agent & copilot instructions, current status, output verification, project identity and ⚠️ critical: tdd required.
arxiv-agent-mcp AGENTS.md
AGENTS.md instructions for tbaraniuk/arxiv-agent-mcp, covering agents.md, roles, test-writer, implementer and per-task loop.