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 grimoire-rs/grimoire --skill upstream-refreshgit clone --depth 1 https://github.com/grimoire-rs/grimoireWrote 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/grimoire-rs/grimoire/upstream-refresh)<a href="https://agentmods.dev/skills/grimoire-rs/grimoire/upstream-refresh"><img src="https://agentmods.dev/badge/skills/grimoire-rs/grimoire/upstream-refresh/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/grimoire-rs/grimoire/upstream-refresh"><img src="https://agentmods.dev/badge/skills/grimoire-rs/grimoire/upstream-refresh.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 | $0.00065 | $0.02335 |
| Opus 5.5 | $0.00026 | $0.00934 |
| Sonnet 5.5 | $0.00013 | $0.00467 |
| Haiku 4.5 | $0.00006 | $0.00233 |
Grade A, and why
upstream-refresh 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 19d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/upstream-refresh — keep grim's upstream facts current
Re-checks the dated upstream claims grim depends on — harness capabilities,
metadata keys, config paths and env vars, specs, forge APIs, the product
landscape, research expiry. Check ledger:
.agents/upstream-checks.md; per-domain
registry: references/domains.md. Design record:
harness-capability-freshness.md.
Modes
/upstream-refresh [<harness>] [--domain <domain>] [--force] [--focus "<text>"]
| Invocation | Targets | Depth |
|---|---|---|
/upstream-refresh |
every non-noop ledger row |
per ladder, never deep |
/upstream-refresh <harness> |
that harness row | deep (the only way to get one) |
--domain vendors |
the 18 harness rows |
per ladder, never deep |
--domain <catalog|specs|forge|landscape|research> |
that one domain row |
per ladder |
--force |
as selected | a noop becomes sweep |
--focus "<surface>" |
every harness row, or only the named harness | that surface only, ladder ignored |
Validate first. The positional token must be a harness name from the
ledger (claude, opencode, copilot, codex, cursor, kiro, junie,
gemini, zed, amp, antigravity, cline, droid, goose, warp,
openclaw, kilo, qoder); --domain must be vendors or a domain row
name. Anything else → stop before any edit, print the valid names. An
unknown token is never read as a focus.
Depth ladder
Never compute ages by hand:
python3 .claude/skills/upstream-refresh/scripts/upstream_stale.py ladder \
[--name <harness>] [--domain <domain>] [--force]
It prints <target> <noop|feed|sweep|deep> <reason> per target. Exit 2 →
relay its stderr and stop. 0 days → noop; 1–2 days → feed (read the
change feed from the cursor); older or never checked → sweep; a named
harness → deep. A reason ending deep due → name that harness in the
report as due for /upstream-refresh <harness>. Every target
noop → print every target checked today — no-op (use --force), edit
nothing. task upstream:stale (the script's report) is the overview.
What ships with it
4 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.
- 19d ago First seen · 180 lines · 65 tokens per session scan A c28484088855
upstream-refresh is a skill published in the GitHub repository grimoire-rs/grimoire (14 stars, last pushed today), licensed Apache-2.0. It adds 65 tokens to every session and 2,335 once invoked, about $0.0003 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 2026-09-28.
Other skills, from other repositories
vuln-scanner
Audit trending repos for real security vulnerabilities and disclose responsibly - scan and route findings (PVR / dependency PR), re-submit queued advisories, and send armed email disclosures.
fork-fleet
Fork divergence monitor - tracks where the fleet's active forks diverge in CODE (unique commits, new/modified skills) and CONFIG (enable/var/model/schedule vs upstream), gated on real change.
pack-submit
Package one of this agent's own skills as a standalone community pack and submit it to the aeon registry as a PR.
shiplog
Recap of everything shipped since the last run - cross-repo PRs, security fixes, star deltas, and X traction, synthesized into a digest article and a ready-to-post shiplog in your voice.
token-pick
One token recommendation and one prediction market pick - scored, quantified, with a skip branch when signals are weak.
autoresearch
Evolve a skill by generating variations, evaluating them, and updating the best version.