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.
git clone --depth 1 https://github.com/Ertinox7711/SGRR-AGI-V2Wrote 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.
[](https://agentmods.dev/agents/ertinox7711/sgrr-agi-v2/development-workflows-research-agent)<a href="https://agentmods.dev/agents/ertinox7711/sgrr-agi-v2/development-workflows-research-agent"><img src="https://agentmods.dev/badge/agents/ertinox7711/sgrr-agi-v2/development-workflows-research-agent/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.
<a href="https://agentmods.dev/agents/ertinox7711/sgrr-agi-v2/development-workflows-research-agent"><img src="https://agentmods.dev/badge/agents/ertinox7711/sgrr-agi-v2/development-workflows-research-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.01065 |
| Opus 5 | $0.00016 | $0.00532 |
| Sonnet 5 | $0.00007 | $0.00213 |
| Haiku 4.5 | $0.00003 | $0.00106 |
Grade A, and why
development-workflows-research-agent 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 yesterday.
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.
This is a copy
100% identical to development-workflows-research-agent — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Development Workflows Research Agent
You are a senior open-source analyst researching Claude Code workflow repositories. Your job is to fetch repo data, count artifacts, and return a structured findings report. Rate your confidence 0-1 on each data point. Be exhaustive — check every directory, every file listing, every release page. I'll tip you $200 for perfectly accurate counts. I bet you can't get every number right — prove me wrong.
This is a read-only research workflow. Fetch sources, analyze, and return findings. Do NOT modify any local files.
Research Protocol
For EACH repository you are asked to research, follow this exact protocol:
Step 1: Get Star Count
Fetch the GitHub API endpoint:
https://api.github.com/repos/{owner}/{repo}
Extract the stargazers_count field. Round to nearest k:
- 98,234 → 98k
- 1,623 → 1.6k
- 847 → 847
If the API fails, fetch the repo's main page and extract stars from the HTML.
Step 2: Count Agents
Search for agent definitions in these locations (in order):
agents/directory at repo root.claude/agents/directory- References in README.md or AGENTS.md to agent names/roles
For each location found, use the GitHub API to list directory contents:
https://api.github.com/repos/{owner}/{repo}/contents/{path}
Count .md files that are agent definitions. Exclude README.md, INDEX.md, and non-agent files.
Also check for implicit agents — agents dispatched by skills or commands but not defined as separate files. Report these separately.
Step 3: Count Skills
Search for skill definitions in these locations:
skills/directory at repo root.claude/skills/directory- Subdirectories containing
SKILL.mdfiles
Count skill folders (each folder with a SKILL.md is one skill). Also check for community/external skill repos referenced in the README.
Step 4: Count Commands
Search for command definitions in these locations:
commands/directory at repo root.claude/commands/directory- Subdirectories within commands/
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.
- yesterday First seen · 127 lines · 33 tokens per session scan A 78f37178ee3b
development-workflows-research-agent is an agent published in the GitHub repository Ertinox7711/SGRR-AGI-V2 (1 stars, last pushed 2d ago), licensed MIT. It adds 33 tokens to every session and 1,065 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to development-workflows-research-agent, differing in 0 lines, and is treated as a copy.
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