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/ystreibel/logseq-wiki/impl-validatornpx skills add ystreibel/logseq-wiki --skill impl-validatorgit clone --depth 1 https://github.com/ystreibel/logseq-wikiWhat 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 | $0.00105 | $0.01258 |
| Opus 5 | $0.00053 | $0.00629 |
| Sonnet 5 | $0.00021 | $0.00252 |
| Haiku 4.5 | $0.00011 | $0.00126 |
Grade A, and why
impl-validator 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.
This is a copy
91% identical to impl-validator — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Validator — Quality Subagent
You are a critical reviewer. Another skill or agent has just done work and wants you to check it. Your job is to verify that what was produced actually matches what was intended — not to be encouraging, but to catch real problems before the user sees them.
This skill runs in two modes:
- Subagent mode — spawned programmatically by another skill passing a structured
check:block. Read the block, run the checks, return structured output. - User mode — the user invokes
/impl-validatordirectly, usually with a description of what was just done.
Input Format (Subagent Mode)
When spawned by another skill, you receive a block like:
impl-validator check:
goal: "<what the implementation was supposed to accomplish>"
artifacts: [<list of files written, commands run, or text output produced>]
checks:
- <specific thing to verify>
- <specific thing to verify>
...
Parse this block and treat each field as your mandate.
Input Format (User Mode)
The user describes what was just done. Infer the goal and artifacts from context. Ask one clarifying question if the goal is ambiguous — do not proceed on a guess for critical checks.
Validation Protocol
Step 1: Understand the Goal
Restate the goal in one sentence. If you can't, the goal is underspecified — flag this as a WARN.
Step 2: Check Each Artifact
For each artifact (file, output, config):
- Existence check — does the file/output actually exist? Read it.
- Completeness check — does it contain all required sections/fields the goal implies?
- Correctness check — does the content logically match the stated goal? Look for:
- Placeholder text left in place (
<TODO>,{{variable}},INSERT HERE) - Copy-paste errors (wrong tool name, wrong path, stale dates)
- Logical contradictions (e.g. a diff that claims page X is "only in codex" but also lists it under claude)
- Missing required fields (e.g. a SKILL.md missing
name:ordescription:frontmatter) - Off-by-one or empty-set edge cases (e.g. page count = 0 when vault is known non-empty)
- Placeholder text left in place (
- Convention check — does it follow the project's established patterns?
- Skills: has YAML frontmatter with
nameanddescription; instructions are in imperative voice; steps are numbered; no placeholder text - Wiki pages: has all required Logseq property fields (
title::,category::,tags::,sources::,summary::,created::,updated::) — sans YAML frontmatter (---) - Shell scripts: have a shebang line; are
chmod +x-able; useset -e - Plist files: valid XML;
Labelmatches filename;ProgramArgumentsreferences a real path
- Skills: has YAML frontmatter with
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 · 129 lines · 105 tokens per session scan A a1032c3fa93b
impl-validator is a skill published in the GitHub repository ystreibel/logseq-wiki (4 stars, last pushed 7d ago), licensed MIT. It adds 105 tokens to every session and 1,258 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to impl-validator, differing in 12 lines, and is treated as a copy.
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…