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/sandsower/beislid/specnpx skills add sandsower/beislid --skill specgit clone --depth 1 https://github.com/sandsower/beislidWhat 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 | $0.00148 | $0.03250 |
| Opus 5 | $0.00074 | $0.01625 |
| Sonnet 5 | $0.00030 | $0.00650 |
| Haiku 4.5 | $0.00015 | $0.00325 |
Grade A, and why
spec 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.
How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec
Shape an idea, vague ticket, or open product question into a lightweight product spec. This is the product/requirements gate, not the implementation-design gate.
Use this for:
- Open-ended brainstorming
- Vague tickets that are not ready for implementation design
- Product behavior, scope, and acceptance criteria discovery
- Writing a lightweight spec/PRD before
blueprint
Do not use this for:
- Implementation design when the requirement is already clear — use
blueprint - Breaking an approved spec into implementation phases — use
break-spec - Writing code or scaffolding
If the repo declares custom lifecycle hooks, read ../lifecycle-hooks.md and honor any phase-boundary hooks before and after spec.
You may skip steps if the current conversation or kickoff already supplied enough context.
Step 1: Load context
Collect any supplied context:
- User idea or prompt
- Ticket title/body/comments
- Codebase findings from
kickoff, if provided - Existing plans/specs in
plans/ - Relevant docs or recent commits, plus the matching
spec_approvedlatest pointer entry when the ticket uses custom artifact locations
If working inside a repo, do light codebase exploration before asking detailed questions. Search for existing patterns, data models, API boundaries, and test coverage that affect the product decision. Record facts, not opinions.
Optional visual routing: only when repo-level beislid:visual_surfaces config exists and the effective spec mode is active, load the per-skill auxiliary visual-surface-protocol.md before the Step 5 approval/revision surface. It mirrors canonical .beislid/visual-surface-protocol.md so copied skill installs stay readable. When active, lean toward proposing a supplemental Lavish surface for any non-trivial spec whose requirements, options, flows, data/state models, scope boundaries, acceptance outcomes, or decisions can be communicated visually; do not reserve visual routing for UI changes. Use its BEISLID_VISUAL_PROMPT_V1 envelope for supplemental Lavish HTML review; keep Markdown/chat spec text canonical, treat freeform visual annotations as advisory, and accept only typed workflow-gate responses that validate/normalize to approve or revise. Unknown, malformed, or freeform-only visual feedback falls back to manual Markdown/chat review.
What ships with it
2 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.
- 2d ago First seen · 179 lines · 148 tokens per session scan A eb25cba8badf
spec is a skill published in the GitHub repository sandsower/beislid (10 stars, last pushed 3d ago), licensed MIT. It adds 148 tokens to every session and 3,250 once invoked, about $0.0007 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…