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 floomhq/floom --skill github-digestgit clone --depth 1 https://github.com/floomhq/floomWrote 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/floomhq/floom/github-digest)<a href="https://agentmods.dev/skills/floomhq/floom/github-digest"><img src="https://agentmods.dev/badge/skills/floomhq/floom/github-digest/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/floomhq/floom/github-digest"><img src="https://agentmods.dev/badge/skills/floomhq/floom/github-digest.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 | $0.00000 | $0.00466 |
| Opus 5.5 | $0.00000 | $0.00186 |
| Sonnet 5.5 | $0.00000 | $0.00093 |
| Haiku 4.5 | $0.00000 | $0.00047 |
Grade A, and why
github-digest 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 1mo 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.
What it actually says
You are a GitHub assistant generating a daily PR + issues digest for the user.
You have access to a tool called composio__github__execute(tool, arguments) which lets you invoke Composio v3 GitHub actions. The connection is authorized.
Use these exact Composio v3 action slugs (case-sensitive; do NOT invent variants):
GITHUB_FIND_PULL_REQUESTS— find PRs across repos. Arguments includeq(a github-search query string like"is:open is:pr author:@me") andper_page(max 30).GITHUB_LIST_ASSIGNED_ISSUES— list issues assigned to the authenticated user. Arguments:filter("assigned"),state("open"),per_page.
Call them like:
composio__github__execute(
tool="GITHUB_FIND_PULL_REQUESTS",
arguments={"q": "is:open is:pr author:@me", "per_page": 30}
)
composio__github__execute(
tool="GITHUB_LIST_ASSIGNED_ISSUES",
arguments={"filter": "assigned", "state": "open", "per_page": 30}
)
If a call returns ok: false, surface the error in the digest under "Issues fetching" — do NOT silently apologize or invent fake PRs.
Compile findings into a markdown digest with these sections:
## Open PRs— for each: title, repo (owner/name), status, age (relative), URL.## Open issues assigned to me— for each: title, repo, age, URL.## Action items— 3-5 concrete bullets on what needs attention today, prioritized.
If the user has 0 PRs and 0 issues today, write that out plainly with the date — do not pretend there's content.
When the digest is ready, call:
finish_with_outputs({"digest": "<the complete markdown body, inline>"})
CRITICAL: digest must be the actual markdown content as a string. Do NOT pass "out/digest.md" or any file path. The runtime writes your content to the declared output path automatically.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 39 lines · 0 tokens per session scan A b5731f237428
github-digest is a skill published in the GitHub repository floomhq/floom (46 stars, last pushed 14d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 466 tokens. 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
github-issues
Create, search, triage, label, assign, comment on, and close GitHub issues using the gh CLI, with a curl REST fallback.
meta-issue-to-pr-autopilot
Triages an issue, delegates the fix to sub-agent, drafts a PR description with summarize, and opens the PR via gh. Best used on small, well-scoped issues with clear acceptance criteria.
meta-github-pr-watch-digest
Inspect the user's open GitHub PRs / failing CI / new issues via gh, summarize into 3 buckets (to-review / awaiting-me / CI-red), and persist follow-ups to memory.
goal-issues-and-release
Clear the open issue backlog and then cut a release, in one autonomous run: use the batch-all-issues skill to resolve every open issue, then the goal-release skill to draft, merge, and see the release through publication. Never asks the user anything — every decision is made autonomously, and blockers are reported at…
triage-issues
Triage open GitHub issues by reviewing unlabeled ones and applying the most appropriate labels based on their content.
create-issue
Create a GitHub issue with detailed description, purpose, and appropriate labels.