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/plunderstruck/scip-query/scip-hyper-optimizationnpx skills add PlunderStruck/scip-query --skill scip-hyper-optimizationgit clone --depth 1 https://github.com/PlunderStruck/scip-queryWrote 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/plunderstruck/scip-query/scip-hyper-optimization)<a href="https://agentmods.dev/skills/plunderstruck/scip-query/scip-hyper-optimization"><img src="https://agentmods.dev/badge/skills/plunderstruck/scip-query/scip-hyper-optimization.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 | $0.00046 | $0.01498 |
| Opus 5 | $0.00023 | $0.00749 |
| Sonnet 5 | $0.00009 | $0.00300 |
| Haiku 4.5 | $0.00005 | $0.00150 |
Grade A, and why
scip-hyper-optimization 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 3d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SCIP Hyper Optimization
This project-local skill restores the last standalone hyper-optimization method from commit bb02f016 and adapts its retired command names to the current scip-query interface.
Use it to make a command, indexer, watcher, workflow, or service faster without changing its observable result. A hyper-optimization campaign is a bounded engineering program that improves runtime, peak memory, or computational work against repeatable measurements. What distinguishes it from general refactoring is that measurements and output identity decide whether a change survives.
Choose the scale
- QUICK — one target, one already-plausible hot operation, and one before/after measurement can settle the decision. Record the run in
docs/benchmarks/runs/YYYY-MM-DD-<target>.jsonl; a separate ledger is optional. - CAMPAIGN — several targets, an unclear bottleneck, cold and warm paths that diverge, memory/runtime tradeoffs, or competing designs. Create the baseline, run history, ledger, profiles, and alternative-design track below.
If naming the operation to change requires investigation, use CAMPAIGN.
Essential terms
A measurement harness is a repeatable experimental setup: commands, fixtures or corpora, cache state, environment facts, and result records. Its defining trait is that another run can reproduce the state being compared.
A run history is a machine-readable measurement record with one row per command, subprocess, or profiled stage. Its defining trait is durability across code changes, so an improvement can be compared to the baseline that motivated it.
A profile span is one named and timed operation inside the target process, such as fingerprinting, compiler startup, conversion, validation, publishing, or cache loading. Its defining trait is that it assigns elapsed work and relevant cardinality to a particular part of the pipeline.
Hierarchical profiling is a bottleneck-localization method that times the whole pipeline, then subdivides only its dominant span. Its defining trait is progressive narrowing until the expensive operation is concrete enough to change.
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.
- 3d ago First seen · 112 lines · 46 tokens per session scan A b37ceb2d5a69
scip-hyper-optimization is a skill published in the GitHub repository PlunderStruck/scip-query (5 stars, last pushed 3d ago), licensed Apache-2.0. It adds 46 tokens to every session and 1,498 once invoked, about $0.0002 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
change-review
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codebase-exploration
Use when exploring, understanding, or answering questions about a codebase that has Repowise indexed (a .repowise/ directory in the project root). Activates for "how does X work", "explain the architecture", "where is Y implemented", "what does this module do", or any task that needs an understanding of structure…
architectural-decisions
Use when encountering questions about WHY code is built a certain way, when about to make architectural changes (new patterns, restructuring, choosing between approaches), or when the user asks about design rationale in a Repowise-indexed codebase (.repowise/ directory exists). Also activates when commit messages or…
code-health
Use when the user asks about code health, code quality, complexity, technical debt, which files are risky or hard to maintain, what to refactor next, untested hotspots, or coverage gaps in a Repowise-indexed codebase (.repowise/ directory exists). Also use to get a before/after health read when planning or finishing a…
pre-modification-check
Use before modifying, refactoring, or deleting files in a codebase that has Repowise indexed (indicated by a .repowise/ directory). Activates when Claude is about to edit code, especially shared utilities, core modules, or files the user didn't explicitly mention. Helps assess impact and avoid breaking things.
pre-modification-check
Use before modifying, refactoring, moving, or deleting files in a Repowise-indexed repository, especially shared utilities, core modules, public APIs, or files the user did not explicitly identify.