Borrowing it
Nothing to install: this file belongs to tphakala/birdnet-go. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tphakala/birdnet-go/main/.agents/skills/preflight/SKILL.mdgit clone --depth 1 https://github.com/tphakala/birdnet-goWrote 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/tphakala/birdnet-go/preflight)<a href="https://agentmods.dev/skills/tphakala/birdnet-go/preflight"><img src="https://agentmods.dev/badge/skills/tphakala/birdnet-go/preflight.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 73 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- high Excessive Agency · line 193 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 5.1 | $0.00055 | $0.07286 |
| Opus 5 | $0.00028 | $0.03643 |
| Sonnet 5 | $0.00011 | $0.01457 |
| Haiku 4.5 | $0.00006 | $0.00729 |
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 7d 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
What ships with it
1 file 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.
- 7d ago First seen · 276 lines · 55 tokens per session scan A e97f9500a242
preflight is a skill published in the GitHub repository tphakala/birdnet-go (1,916 stars, last pushed today), with no licence file. It adds 55 tokens to every session and 7,286 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 2026-09-01.
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Prepare, create, update, and monitor pixiv-cli pull requests using the repository template, verification checklist, review handoff, and authorization boundaries. Use when drafting a PR body, opening or editing a PR, requesting review, checking readiness, or handing a merged PR to release preparation.
gh-pr
Writes clear pull request descriptions from the current branch diff against a base branch. Defaults to main, but supports dev or any other user-specified comparison branch. Use when the user asks for a PR description, pull request summary, or a markdown write-up for changes against a base branch.
workflow-pr-review
Use when reviewing a remote GitHub PR — a first-pass peer review, or a followup re-check after the owner has addressed feedback. Fetches into an ephemeral worktree, runs the reviewer agent against the updated diff with a Review Decision footer instruction, deduplicates findings against existing review threads (±5-line…
workflow-address-feedback
Use when a PR owner wants to address review feedback — fetches outstanding threads and general comments, presents a per-item triage (ADDRESSED / CLARIFIED / DEFERRED), applies fixes via the Edit tool, commits via workflow-commit-and-pr, resolves review threads via GraphQL resolveReviewThread (those without a thread…
workflow-pr-review-post
Posting core shared by workflow-pr-review (both first-pass and followup modes) and the specialist /swe-workbench:review PR-mode sub-flow — takes a normalized findings/decision/byline payload, dedupes against existing review threads (±5-line fuzzy match + Jaccard ≥ 0.4), posts new inline or PR-level comments, applies…