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 skills add desplega-ai/agent-swarm --skill create-prgit clone --depth 1 https://github.com/desplega-ai/agent-swarmWrote 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/desplega-ai/agent-swarm/create-pr)<a href="https://agentmods.dev/skills/desplega-ai/agent-swarm/create-pr"><img src="https://agentmods.dev/badge/skills/desplega-ai/agent-swarm/create-pr/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/desplega-ai/agent-swarm/create-pr"><img src="https://agentmods.dev/badge/skills/desplega-ai/agent-swarm/create-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00022 | $0.01051 |
| Opus 5.5 | $0.00009 | $0.00420 |
| Sonnet 5.5 | $0.00004 | $0.00210 |
| Haiku 4.5 | $0.00002 | $0.00105 |
Grade A, and why
create-pr 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.
How it starts
The opening of the file, as written. The whole thing — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Pull Request / Merge Request
Create a PR (GitHub) or MR (GitLab) from the current branch with an auto-generated title and description.
Provider detection: Check the remote URL:
- If
github.com→ useghCLI - If
gitlab.comorgitlab.→ useglabCLI
Arguments
base-branch(optional): Branch to merge into (defaults tomainor repo default)
Prerequisites
You should be working in a repository cloned to /workspace/personal/<repo-name>.
Workflow
- Verify state — confirm you're in a git repo, not on main/master, and have commits to push.
- Run PR checks (MANDATORY) — Run ALL checks listed in the "PR Checks" section of your Repository Guidelines. Run each command/task sequentially. If ANY check fails, fix the issue and re-run until all pass. If no guidelines are defined, check the project's CLAUDE.md for a pre-PR checklist and run those. Do NOT proceed until all checks pass.
- Push the branch —
git push -u origin HEAD - Gather context — review commit messages and changed files since diverging from base.
- Generate title and description. Follow the conventions of the repository you are working in, not a fixed format:
- Title: Concise summary (conventional commit style if the repo uses it)
- Description: If the repo has a PR/MR template, use its headings as the structure and fill every section. GitHub looks for
pull_request_template.mdin.github/,docs/, or the repo root (plus an optionalPULL_REQUEST_TEMPLATE/directory), and falls back to the org's.githubrepo. GitLab uses.gitlab/merge_request_templates/. Also follow any PR rules in the repo'sCLAUDE.md,AGENTS.md, orCONTRIBUTING.md. If the repo defines none, include: summary of changes, notable items, testing done, related issues. - Show the change, do not narrate it. Aim for about 250 prose words; code blocks, mermaid, tables and
<details>do not count. No file-by-file changelog: that belongs in your task output. - Review map: build it from
git diff --stat <base>...HEAD. One row per area, biggest risk first, with(+N/-M), a depth (🔍 deep, 👀 skim, ⏭ skip for tests and generated files) and what could break. - Change outline: 1 or 2 views of the shape of the change. Pseudocode with
+/-lines for logic, mermaid for flow, a tree with paths on the nodes for structure. - Swarm provenance (when you run in the swarm): fill it from your task context. Link the task (
$APP_URL/tasks/<taskId>) and its tree ($APP_URL/sessions/<rootTaskId>), the Slack permalink of the ask if the task came from Slack, any workflow run, and the plan or research as its agent-fs live app link (${AGENT_FS_LIVE_URL}/file/~/<org>/<drive>/<path>). These auth-gated links go in this section only. - Media: images and mp4s as GitHub user attachments (
github-attachskill), docs as the agent-fs live app link under Swarm provenance (anagent-fs share-createlink only when the requester asks for one or a reader has no agent-fs login). Never a presigned agent-fs URL for docs or videos.
- Create the PR/MR using
gh pr createorglab mr create.gh pr create --bodydoes not apply the repo template, so write the filled description to a file and pass it with--body-file <file>. - Check CI status — After creating the PR, wait ~30 seconds, then check CI with
gh pr checks <pr-number>(GitHub) orglab mr view --json pipelines(GitLab). If any check is failing, investigate the failure, fix it, push the fix, and re-check. Repeat until CI is green. - Report the PR/MR URL and CI status.
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 Changed 1f5966bd01f0
- 18d ago Changed · +6 lines dfbc18a47e00
- 1mo ago Changed 2e88e3675172
- 1mo ago First seen · 40 lines · 22 tokens per session scan A d7520f1f6215
create-pr is a skill published in the GitHub repository desplega-ai/agent-swarm (944 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 1,051 once invoked, about $0.0001 per session on Opus 5.5. 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 skills, from other repositories
pr-body
A tool that reviews all commits on the current branch and creates or updates a pull request title and description. A pull request is a proposed code change submitted for review.
github
Interact with GitHub using the gh CLI. Use gh issue, gh pr, gh run, and gh api for issues, PRs, CI runs, and advanced queries.
beevibe-pre-task-setup
Cold-start git workspace setup for a fresh beevibe task. Use at the start of a session whose intent has a block but NO or block — i.e. the first dispatch of this task. Checks for an existing repo clone, pulls the base branch if present (clone if missing), prunes any per-task worktrees from earlier tasks whose work has…
security-observability
A read-only tool for examining security events already saved by agent-sec-cli, a command-line security log. It can connect those events to an agent session, run, or trace.
add-backend
Guide for adding a backend (Rust or Python) to the agent-sec-core security middleware. Use when creating new backends, integrating Rust or Python code into the security middleware, or extending with new backend actions.
skill-ledger
A security record for agent skills, which are reusable instruction packages for coding agents. It shows their status, reviews risk exposure, and can certify them with quick or user-approved deeper scans.