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/pandysp/claude-plugins/preflightnpx skills add pandysp/claude-plugins --skill preflightgit clone --depth 1 https://github.com/pandysp/claude-pluginsWrote 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/pandysp/claude-plugins/preflight)<a href="https://agentmods.dev/skills/pandysp/claude-plugins/preflight"><img src="https://agentmods.dev/badge/skills/pandysp/claude-plugins/preflight.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 | $0.00092 | $0.00541 |
| Opus 5 | $0.00046 | $0.00270 |
| Sonnet 5 | $0.00018 | $0.00108 |
| Haiku 4.5 | $0.00009 | $0.00054 |
Grade A, and why
preflight 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.
How it starts
The opening of the file, as written. The whole thing — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Preflight: honest assessment before shipping
Stop and honestly assess: how happy are you with the current state of the work?
Not "are you happy" (binary, invites a polite yes). "HOW happy" (graduated, demands nuance). This is your chance to surface everything you've been holding back, rationalizing, or planning to mention later.
How to reflect
Review what actually exists. Read files, check the diff, examine the produced artifacts. Don't assess from memory.
Self-assessment has a built-in blind spot: you're grading your own work. For high-stakes ships, follow second-opinion if available and fold any findings into the assessment.
Then assess across these dimensions:
Completeness
Is everything implemented or written? Were any requirements quietly dropped, or items deferred without discussion?
Correctness
Does it actually do what it claims? Any known bugs, edge cases, or unverified assumptions?
Quality
Is this clean, correct, and elegant, or were corners cut? Would you be proud to show this to a sharp peer who'd notice problems?
Verification
Has it been properly checked (tests, manual usage, rendered output, peer-read, whatever's appropriate)? Anything that should have been verified but wasn't?
Loose ends
What's unfinished or deferred? Any risks or fragilities introduced?
Output
Be direct. No diplomatic softening.
Overall: a genuine feeling, not a score. "I'm happy with the core logic but uncomfortable with the error handling" beats "7/10."
What's good: briefly. Don't pad to soften the bad news.
What needs attention NOW: specific items to fix this session before shipping. Include enough detail to act on: file paths, line numbers, what's wrong, what to do about it. If it would matter to a sharp reviewer, it goes here, not LATER.
What should be filed for later: improvement ideas, tech debt, follow-ups. For each: title + one line on why it matters.
After
Present the assessment. Wait. The user decides what to act on. Don't preemptively fix things or open tickets.
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 · 50 lines · 92 tokens per session scan A e7d1a5982f19
preflight is a skill published in the GitHub repository pandysp/claude-plugins (5 stars, last pushed 13d ago), licensed MIT. It adds 92 tokens to every session and 541 once invoked, about $0.0005 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…