Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/hybridlabor-api/bdb-dev-optimized-agent-skillsnpx agentmods add skills/hybridlabor-api/bdb-dev-optimized-agent-skills/agent-manager-skillWrote 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/skills/hybridlabor-api/bdb-dev-optimized-agent-skills/agent-manager-skill)<a href="https://agentmods.dev/skills/hybridlabor-api/bdb-dev-optimized-agent-skills/agent-manager-skill"><img src="https://agentmods.dev/badge/skills/hybridlabor-api/bdb-dev-optimized-agent-skills/agent-manager-skill/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/skills/hybridlabor-api/bdb-dev-optimized-agent-skills/agent-manager-skill"><img src="https://agentmods.dev/badge/skills/hybridlabor-api/bdb-dev-optimized-agent-skills/agent-manager-skill.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 | $0.00030 | $0.00659 |
| Opus 5 | $0.00015 | $0.00329 |
| Sonnet 5 | $0.00006 | $0.00132 |
| Haiku 4.5 | $0.00003 | $0.00066 |
Grade A, and why
agent-manager-skill 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.
How it starts
The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Manager Skill
When to Use
Use this skill when you need to:
- run multiple local CLI agents in parallel (separate tmux sessions)
- start/stop agents and tail their logs
- assign tasks to agents and monitor output
- schedule recurring agent work (cron)
Prerequisites
Install agent-manager-skill in your workspace:
git clone https://github.com/fractalmind-ai/agent-manager-skill.git
Common commands
python3 agent-manager/scripts/main.py doctor
python3 agent-manager/scripts/main.py list
python3 agent-manager/scripts/main.py start EMP_0001
python3 agent-manager/scripts/main.py monitor EMP_0001 --follow
python3 agent-manager/scripts/main.py assign EMP_0002 <<'EOF'
Follow teams/fractalmind-ai-maintenance.md Workflow
EOF
Notes
- Requires
tmuxandpython3. - Agents are configured under an
agents/directory (see the repo for examples).
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
1. Overview
This skill provides domain-specific logic and rules for its respective BDB pipeline component to ensure standardization across multi-agent workflows.
3. Core Process
- Read the provided context and ensure preconditions are met.
- Run the required script or tool and confirm the state change.
- Verify exit codes, file modifications, or DB counts to guarantee success before reporting completion.
4. Common Rationalizations
| Rationalization | Reality |
|---|---|
| "The code change was small, so I skipped updating OpenWiki docs." | Every state change must be reflected in the relevant system records. |
| "The ingest script exited without an error, so the memB index must be updated." | Silent failures happen; explicit verification of the side effect is mandatory. |
| "I'll let the /startcycle proceed without a defined rollback path." | Proceeding without a rollback path corrupts the workflow integrity and safety. |
| "I trust the cached agent registry instead of rescanning after a skill change." | Caches stale out quickly; explicit rescans prevent ghost failures. |
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.
- 7d ago First seen · 75 lines · 30 tokens per session scan A 30da41746b0f
agent-manager-skill is a skill published in the GitHub repository hybridlabor-api/bdb-dev-optimized-agent-skills (6 stars, last pushed 5d ago), licensed Apache-2.0. It adds 30 tokens to every session and 659 once invoked, about $0.0002 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 2026-09-03.
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