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 agentmods add skills/harshanandak/forge/shownpx skills add harshanandak/forge --skill showgit clone --depth 1 https://github.com/harshanandak/forgeWrote 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/harshanandak/forge/show)<a href="https://agentmods.dev/skills/harshanandak/forge/show"><img src="https://agentmods.dev/badge/skills/harshanandak/forge/show.svg" alt="Measured on agentmods" 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 | $0.00048 | $0.00376 |
| Opus 5 | $0.00024 | $0.00188 |
| Sonnet 5 | $0.00010 | $0.00075 |
| Haiku 4.5 | $0.00005 | $0.00038 |
Grade A, and why
show 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 4d 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
forge show
Purpose
Retrieve everything Forge knows about one issue so you can act on it with full context: the description, acceptance criteria, current status, blocking and blocked-by links, and any prior comments.
When to Use
- Right after picking an id from
forge ready, to understand the task. - Before commenting, to see what has already been recorded.
- Before closing, to confirm the acceptance criteria are met.
Command
forge show <id> # full detail for one issue
forge issue show <id> # equivalent issue-scoped form
Instructions
- Run
forge show <id>with the issue id you want to inspect. - Read the description and acceptance criteria to understand the goal.
- Check the dependency links to confirm the issue is actionable.
- Review existing comments so you do not repeat prior context.
Example
$ forge show forge-142
forge-142 Wire kernel selector into dispatch
status: in_progress
depends on: forge-130 (closed)
---
Route `forge <command>` through the kernel selector when the kernel backend
is active. Acceptance: multi-id close works end to end.
Success Criteria
- The issue's description and status are understood before acting.
- Dependency state is confirmed actionable.
Related Skills
- ready: find which issue id to show.
- comment: record findings after reviewing the issue.
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.
- 4d ago First seen · 61 lines · 48 tokens per session scan A 634e457fbc6d
show is a skill published in the GitHub repository harshanandak/forge (4 stars, last pushed 4d ago), licensed MIT. It adds 48 tokens to every session and 376 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…