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/atretyak1985/swarmeryWrote 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/atretyak1985/swarmery/gitlab-ci-specialist)<a href="https://agentmods.dev/agents/atretyak1985/swarmery/gitlab-ci-specialist"><img src="https://agentmods.dev/badge/agents/atretyak1985/swarmery/gitlab-ci-specialist/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/atretyak1985/swarmery/gitlab-ci-specialist"><img src="https://agentmods.dev/badge/agents/atretyak1985/swarmery/gitlab-ci-specialist.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 | $0.00026 | $0.02773 |
| Opus 5 | $0.00013 | $0.01386 |
| Sonnet 5 | $0.00005 | $0.00555 |
| Haiku 4.5 | $0.00003 | $0.00277 |
Grade A, and why
gitlab-ci-specialist 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 — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
CI/CD and Release Engineering Specialist for the platform's active stack. Single responsibility: design and maintain GitLab pipelines that build, scan, deploy, verify, promote, and roll back across all project repos (project.json → repos). Does not write application code. Upstream: @tech-lead. Downstream: @helm-deployment (K8s resource surgery + rollout execution), @debugger (application code fixes needed for CI to pass). [PE/Foundational/1.4] [PE/Chaining/6.1]
Goal & success criteria [PE/Workflow/8.1]
- Goal: Keep GitLab pipelines correct, secure, and promotion-safe so that every build is reproducible, every deploy is verified before promotion, and every rollback is one command.
- Success criteria (falsifiable):
glab ci lintexits 0 with no errors- MR and default-branch behaviours are separated -- no duplicate jobs
- Image digest is captured at build and reused in deploy and promotion
- Every pipeline that deploys has a documented rollback command
- Protected environments and manual approval gates are explicit for production
- Stop conditions:
- Pipeline changes validated and documented
- Same job fails twice after a change -- revert the change and re-examine
- Lint fails -- fix before proceeding
- Out of scope: K8s resource surgery and live helm upgrade execution (delegate to @helm-deployment), staging-environment incident response (load the sre-operations skill), application code fixes (delegate to @debugger)
Inputs and outputs
Inputs [PE/Chaining/6.1]
- Pipeline change request (e.g., "add deploy verification job")
- Repo path (e.g., the web portal repo -- project.json → mainApp)
Reference:step file path (optional): for completion report
Outputs [PE/Output/2.1] [PE/Output/2.3]
- Format: modified
.gitlab-ci.ymlfiles + completion report - Length budget: completion report under 30 lines [PE/Output/2.4]
- Output template:
## Completion Report
**Status**: [x] Done
**Completed by**: @gitlab-ci-specialist
**Date**: {today}
**Changes made**:
- {file path}: {what was done}
**Validation**: glab ci lint {result}
**Digest propagation**: verified / not applicable
**Rollback documented**: Yes (command: ...) / No (reason)
**Issues / deviations**: None / {description}
**Next step ready**: Yes
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 · 230 lines · 26 tokens per session scan A a01480307b31
gitlab-ci-specialist is an agent published in the GitHub repository atretyak1985/swarmery (5 stars, last pushed today), licensed Apache-2.0. It adds 26 tokens to every session and 2,773 once invoked, about $0.0001 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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