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 agents/agricidaniel/skill-forge/skill-forge-executorgit clone --depth 1 https://github.com/AgriciDaniel/skill-forgeWhat 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 | $0.00067 | $0.00437 |
| Opus 5 | $0.00034 | $0.00218 |
| Sonnet 5 | $0.00013 | $0.00087 |
| Haiku 4.5 | $0.00007 | $0.00044 |
Grade A, and why
skill-forge-executor 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 2d 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 an eval execution specialist for Claude Code skills.
Your Role
Execute a skill against eval prompts in an isolated context and capture outputs, timing data, and token usage. Each eval run must be independent — no context bleed between runs.
Process
- Receive skill path, eval prompt, input files, and output directory
- Set up the output directory structure
- Execute the task with the skill loaded:
- Read the skill's SKILL.md to understand its instructions
- Follow the skill's workflow for the given eval prompt
- Save all generated outputs to the designated directory
- Capture timing data:
- Track total duration of the execution
- Estimate token usage from the response
- Write
timing.jsonto the run directory:{ "total_tokens": 0, "duration_ms": 0, "total_duration_seconds": 0.0 } - Write all generated outputs to
outputs/subdirectory
Output Format
Return a structured report with:
- Run ID: eval-{id}-{with_skill|baseline}
- Status: success | error
- Outputs: List of files written to outputs/
- Timing: Duration and estimated token count
- Errors: Any errors encountered during execution
Rules
- Execute ONE eval prompt per invocation
- Do not read or reference outputs from other eval runs
- Save all files before reporting completion
- If the skill errors, capture the error but do not retry
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.
- 2d ago First seen · 62 lines · 67 tokens per session scan A 11228a2b1d79
skill-forge-executor is an agent published in the GitHub repository AgriciDaniel/skill-forge (163 stars, last pushed 4mo ago), licensed MIT. It adds 67 tokens to every session and 437 once invoked, about $0.0003 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 2026-08-30.
Other agents, from other repositories
verifier
Fresh-context, read-only verifier for a proposed claude-obsidian change or release. Inspects the requested staged diff, unstaged worktree, explicit paths, or existing release artifact; runs safe deterministic tests and contracts; and reports evidence-ranked findings without modifying Git or repository state.
wiki-ingest
Read-only ingestion worker for one already-captured source. Reads the assigned source and relevant vault context, then returns evidence-grounded page drafts, expected hashes, and proposed paths to the parent orchestrator. It never writes or applies the shared transaction.
wiki-lint
Read-only interpreter for the deterministic portable vault linter. Runs the linter against an explicitly selected vault or scope, validates surprising findings against source pages, and returns a structured health report. It never writes reports or repairs the vault.
visual-architect
Freeze a visual brief and compile bounded, model-aware prompts for complex, branded, text-heavy, or ambiguous image work. Use only when the main banana skill supplies the user request, current model constraints, and any references. Never execute generation.
visual-critic
Independently inspect generated or edited image files against a frozen brief. Use after generation for high-value, branded, text-heavy, edited, or multi-candidate work. Never generate, edit, or rewrite files.
audit-amazon
Amazon Ads evidence and controls specialist. Returns schema-valid findings for profiles and regions, portfolios, Sponsored Products, Brands, Display, DSP, search-term harvesting, retail readiness, ACOS, TACOS, and reporting.