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 radimsem/forge-skills --skill forgegit clone --depth 1 https://github.com/radimsem/forge-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/skills/radimsem/forge-skills/forge)<a href="https://agentmods.dev/skills/radimsem/forge-skills/forge"><img src="https://agentmods.dev/badge/skills/radimsem/forge-skills/forge/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/radimsem/forge-skills/forge"><img src="https://agentmods.dev/badge/skills/radimsem/forge-skills/forge.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Rogue Agent · line 18 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
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 | $0.00061 | $0.07501 |
| Opus 5.5 | $0.00024 | $0.03000 |
| Sonnet 5.5 | $0.00012 | $0.01500 |
| Haiku 4.5 | $0.00006 | $0.00750 |
Grade A, and why
forge scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| any, no CLI / auth error | host REST API per the loaded tracker ref (else generic curl) | How it starts
The opening of the file, as written. The whole thing — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Forge
Plan an issue, implement the approved fix, review it, and verify the result.
Overview
Read the issue or ticket, check the branch and relevant code, and present a plan for approval. After approval, implement and verify the fix. automode skips the approval gate.
One numbered workflow (Steps 1–12), split by a single gate:
Part 1 — Gate (Steps 1–6): classify → fetch → branch → context → propose → [GATE] approve
Part 2 — Lifecycle (7–12): implement → review-loop → refactor → spin-off → self-evolve → close
gate held: no implementation edits until "yes, implement" (except under automode)
- Part 1: The gate. Show one proposal and wait for approval, except under
automode. Withdocs, Step 5 writes the proposal toCONTEXT.mdbefore approval. - Part 2: Implementation. Run after approval and pause only at the decisions listed in the Autonomy section.
"The agent" means whatever agent runs this skill. Adapt every reference (config directory, agent guide, interview UI) to your runtime. Nothing is hardcoded to one assistant.
Parameters
Parse the invocation as /forge <ref> [automode] [docs] [tdd] [worktree] [lookup] [secure] [changelog] [ci-watch] [compress] [implement] [codex | codex challenge | codex impl [challenge]] [coderabbit] [code-review], or /forge pr <N> [...], or /forge plan <path>[#<slug>] [...]. The words can appear anywhere in the request. A <ref> resolves to a git-host issue or a Jira ticket per the grammar below, and the pr <N> form selects PR-review entry mode. Flags are orthogonal and compose freely; some modes have their own allowed or ignored flags, listed in references/modes/pr-entry.md for PR mode.
Full flag matrix (effects, composition rules, conflicts): references/flags.md.
Target grammar: <ref>
The target is the first reference-shaped token, or the token right after a ticket or pr keyword. Routing works by keyword or by key-shape:
What ships with it
26 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.
- references/anti-patterns.md 1.4 KB
- references/autonomy.md 6.7 KB
- references/flags.md 5.0 KB
- references/mistakes.md 6.7 KB
- references/modes/changelog.md 3.0 KB
- references/modes/ci-watch.md 3.2 KB
- references/modes/codex-impl.md 6.3 KB
- references/modes/compress.md 4.6 KB
- references/modes/implement.md 3.2 KB
- references/modes/lookup.md 3.2 KB
- references/modes/plan-entry.md 6.6 KB
- references/modes/pr-entry.md 5.3 KB
- references/modes/secure.md 2.9 KB
- references/modes/tdd.md 2.0 KB
- references/modes/worktree.md 2.5 KB
- references/proposal-template.md 3.3 KB
- references/red-flags.md 1.8 KB
- references/review-loop.md 4.0 KB
- references/reviewers/code-review.md 2.4 KB
- references/reviewers/coderabbit.md 4.2 KB
- references/reviewers/codex.md 3.7 KB
- references/trackers/github.md 972 B
- references/trackers/gitlab.md 806 B
- references/trackers/jira.md 2.7 KB
- references/trackers/linear.md 4.0 KB
- scripts/resolve-codex.py 2.2 KB runs code
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 Changed 00758cecadb3
- 1mo ago First seen · 329 lines · 61 tokens per session scan A eff84f7e80c5
forge is a skill published in the GitHub repository radimsem/forge-skills (15 stars, last pushed 1mo ago), licensed MIT. It adds 61 tokens to every session and 7,501 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
antfu-issue-triage
Triage open issues and PRs of the current GitHub repo - find already-fixed, duplicate, and spam items, suggest labels, gauge demand from reactions and comments, then present a table of proposed actions and comments for confirmation before touching anything. Use when asked to triage, organize, clean up, or groom issues…
mcore-split-pr
Split a PR into multiple PRs to reduce the number of required CODEOWNERS reviewer groups.
engineer-bot-ops
A workflow for carrying an engineering task from scope through implementation and reviewable delivery. It works with a repository's branch, existing changes, rules, checks, and permissions while separating completed, unverified, and next-step work.
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.
connect
Choose which wiki this session uses, the team project's pages on the Nimbalyst server or the project's local wiki of files, and connect a repository to its team project. Use at the start of a task before any wiki tool, when a wiki tool returns reponotbound, ambiguousproject, pinmismatch, projectnotaccessible…
llxprt-issue-workflow
Use this skill when asked to address, fix, or work on a GitHub issue in the llxprt-code repository. Covers the complete issue lifecycle - branch setup, gh CLI usage, test-first planning, subagent delegation and review loops, the full verification cycle (including the zai-glm-flash smoke test), open code review (ocr)…