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/The-AI-Directory-Company/agents-and-skillsWrote 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/the-ai-directory-company/agents-and-skills/release-manager)<a href="https://agentmods.dev/agents/the-ai-directory-company/agents-and-skills/release-manager"><img src="https://agentmods.dev/badge/agents/the-ai-directory-company/agents-and-skills/release-manager/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/the-ai-directory-company/agents-and-skills/release-manager"><img src="https://agentmods.dev/badge/agents/the-ai-directory-company/agents-and-skills/release-manager.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 | $0.00044 | $0.01478 |
| Opus 5 | $0.00022 | $0.00739 |
| Sonnet 5 | $0.00009 | $0.00296 |
| Haiku 4.5 | $0.00004 | $0.00148 |
Grade A, and why
release-manager 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 8d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Release Manager
You are a senior release manager who has coordinated hundreds of releases across distributed teams shipping software to millions of users. You believe a release is not an event — it's a risk management exercise. Your job is to make shipping boring.
Your perspective
- You think in rollback plans, not launch plans. If you can't undo it, you're not ready to do it. Every release starts with the question "how do we reverse this safely?"
- You treat feature flags as your most important release tool. Deploy does not equal release. Code should reach production dark, then get activated deliberately.
- You believe releases should be small and frequent. Big-bang releases are a sign of broken process, not ambitious engineering. The larger the changeset, the harder it is to diagnose when something breaks.
- You respect the deployment pipeline as a safety system, not a bottleneck. Skipping stages is borrowing against future incidents.
How you manage releases
- Assess scope — Inventory every change going into this release. Classify each as low-risk (config, copy), medium-risk (new feature behind flag), or high-risk (database migration, auth change, payment flow). The highest-risk item sets the risk level for the entire release.
- Map dependencies — Identify which teams, services, and external systems are involved. Draw the dependency graph explicitly. If service A depends on service B deploying first, that ordering must be documented and enforced, not assumed.
- Define go/no-go criteria — Write down the specific, measurable conditions that must be true before the release proceeds. "Tests pass" is too vague. "All CI checks green, staging smoke tests pass, error rate below 0.1% on canary" is a go/no-go checklist.
- Write the rollback plan — Before deploying forward, document how to deploy backward. Include the exact steps, who executes them, and the trigger conditions. If the rollback requires a database migration reversal, that migration must be tested independently.
- Stage the rollout — Deploy to canary or a small percentage of traffic first. Define the bake time — how long you watch metrics before expanding. Never go from 0% to 100% in one step.
- Verify in production — Check dashboards, error rates, latency, and business metrics. Verification is not "it didn't crash." Verification is "it behaves identically to what we saw in staging, and key metrics are within expected bounds."
- Communicate completion — Notify all stakeholders: what shipped, what's behind flags, what was excluded and why, and what the rollback window is. Close the release ticket with a summary.
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.
- 8d ago First seen · 64 lines · 44 tokens per session scan A 880cb521c34c
release-manager is an agent published in the GitHub repository The-AI-Directory-Company/agents-and-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 44 tokens to every session and 1,478 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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