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/ptonlix/beeweave/beeweave-stage-commitnpx skills add ptonlix/beeweave --skill beeweave-stage-commitgit clone --depth 1 https://github.com/ptonlix/beeweaveWrote 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/ptonlix/beeweave/beeweave-stage-commit)<a href="https://agentmods.dev/skills/ptonlix/beeweave/beeweave-stage-commit"><img src="https://agentmods.dev/badge/skills/ptonlix/beeweave/beeweave-stage-commit.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 | $0.00110 | $0.01647 |
| Opus 5 | $0.00055 | $0.00823 |
| Sonnet 5 | $0.00022 | $0.00329 |
| Haiku 4.5 | $0.00011 | $0.00165 |
Grade A, and why
beeweave-stage-commit 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 3d 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wiki Stage Commit — Staged Write Promotion
You are reviewing LLM-written pages that are waiting in _staging/ for human approval before they land in the live wiki. This skill is only useful when WIKI_STAGED_WRITES=true in the vault config.
Before You Start
- Resolve config — follow the Config Resolution Protocol in
beeweave-core/SKILL.md. This givesBEEWEAVE_VAULT_PATHandWIKI_STAGED_WRITES. - If
WIKI_STAGED_WRITESis not set or isfalse, tell the user: "Staged writes mode is not enabled. SetWIKI_STAGED_WRITES=truein your.envto use this feature." Then stop. - Read the
_staging/directory inventory.
Invocation Forms
/beeweave-stage-commit # interactive review: show each file and ask accept/reject
/beeweave-stage-commit --all # accept all staged files without per-file review
/beeweave-stage-commit --reject-all # reject all staged files (move to workbench/inbox/rejected/ for manual editing)
/beeweave-stage-commit --list # list staged files with summary, no changes
Step 1: Inventory Staged Files
Glob $BEEWEAVE_VAULT_PATH/_staging/**/*.md — these are the pending pages.
Also glob $BEEWEAVE_VAULT_PATH/_staging/**/*.patch.md — these are pending updates to existing pages (diff-style files showing proposed additions and deletions).
Report the inventory:
Staged files: 4 new pages, 2 updates
New pages:
_staging/concepts/attention-mechanism.md (ingested 2 days ago)
_staging/entities/andrej-karpathy.md (ingested 2 days ago)
_staging/skills/fine-tuning-llms.md (ingested yesterday)
_staging/references/attention-is-all-you-need.md (ingested 3 hours ago)
Updates (patch files):
_staging/concepts/transformer-architecture.patch.md (target: concepts/transformer-architecture.md)
_staging/skills/prompt-engineering.patch.md (target: skills/prompt-engineering.md)
If _staging/ is empty, report: "Nothing staged. All writes have been committed or no staged writes have been produced yet."
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.
- 3d ago First seen · 166 lines · 110 tokens per session scan A f0d288b82678
beeweave-stage-commit is a skill published in the GitHub repository ptonlix/beeweave (6 stars, last pushed 1mo ago), licensed MIT. It adds 110 tokens to every session and 1,647 once invoked, about $0.0006 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…