Borrowing it
Nothing to install: this file belongs to PascaleBeier/hitkeep. 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/PascaleBeier/hitkeep/main/.agents/skills/hitkeep-hygiene-generated-data/SKILL.mdgit clone --depth 1 https://github.com/PascaleBeier/hitkeepWrote 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/pascalebeier/hitkeep/hitkeep-hygiene-generated-data)<a href="https://agentmods.dev/skills/pascalebeier/hitkeep/hitkeep-hygiene-generated-data"><img src="https://agentmods.dev/badge/skills/pascalebeier/hitkeep/hitkeep-hygiene-generated-data/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pascalebeier/hitkeep/hitkeep-hygiene-generated-data"><img src="https://agentmods.dev/badge/skills/pascalebeier/hitkeep/hitkeep-hygiene-generated-data.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00052 | $0.00397 |
| Opus 5.5 | $0.00021 | $0.00159 |
| Sonnet 5.5 | $0.00010 | $0.00079 |
| Haiku 4.5 | $0.00005 | $0.00040 |
Grade A, and why
hitkeep-hygiene-generated-data 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 1mo 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.
What it actually says
HitKeep Generated Data Hygiene
Treat AGENTS.md as policy and load $hitkeep-development plus $hitkeep-qa.
Run canonical refreshers
Refresh the AI-agent, spam, and IP metadata families independently through the corresponding ai-agents, spam, and ipmeta targets of go run ./cmd/data-refresh. The duckdb target maintains the separate signed extension bundle; release builds keep the standalone updater's offline -check command.
Discover exact invocation, required container/runtime, inputs, and outputs from the tracked scripts, generator entry points, workflows, and live hk catalog. Execute those surfaces; do not recreate downloads or transformations. Never print or persist credentials. Treat downloaded content as untrusted and stop on a changed source contract, checksum failure, malformed input, or unexpectedly unbounded output.
Run the families independently so one failure does not hide the other results. Do not hand-correct generated output. If a generator fails, diagnose and report it; change generator code only when the user has authorized fixing the generator itself.
Review and validate
For each family, record the canonical surface, upstream source/version metadata when available, changed generated files, and before/after size or record-count signals. Inspect diffs for truncation, schema drift, surprising deletions, binary bloat, private data, and unrelated changes. Rerun when practical and require an empty second diff as a determinism check.
Use the live QA planner for focused generator tests and generated-data integrity gates. If delegated, leave consolidated PR-parity QA to the parent. Return per-family status, stable gate IDs, run IDs, and blockers.
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.
- 1mo ago First seen · 23 lines · 52 tokens per session scan A afa047af9809
hitkeep-hygiene-generated-data is a skill published in the GitHub repository PascaleBeier/hitkeep (98 stars, last pushed 4d ago), licensed MIT. It adds 52 tokens to every session and 397 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-27.
Other skills, from other repositories
streamsql
A Chinese-language guide to StreamSQL, a SQL-based way to process continuously arriving data in RuleGo. It covers filtering, transformations, time windows, joins, change tracking, cumulative values, and event-pattern matching.
pi-loop-forensics
Diagnose pi-go agent loops and degenerate turns — "agent loop aborted", runaway thinking with no tool calls, repeated phrases. Discriminates genuine model repetition collapse from a race, a tool-parse failure, or a too-low guard, and A/B replays a seed session across providers.
nightly-session-watch
Nightly sweep of the last 24h of pi-go sessions — anomalous runs, loop aborts, tool error rates, token waste, real prompt-token spend, and whether the observation and palace pipelines are still recording. Triages each finding to the specialist skill that diagnoses it. Use for an unattended daily health check, or on…
memory-status
Show MemPalace memory system status — drawer counts, wings, rooms, knowledge graph stats, and embedding model state.
migration-helper
Analyze GORM model changes, estimate resulting schema (DDL) differences, and propose safe migration steps with verification guidance.
code-review-pi
Review code for quality, run linters, check test coverage, fix issues, and enforce gates. Save the final report to ./specs/issues/003-code-review-pi/PROMPT.md. Use before committing changes.