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/cratis/verticalslices/review-performancenpx skills add Cratis/VerticalSlices --skill review-performancegit clone --depth 1 https://github.com/Cratis/VerticalSlicesWrote 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/cratis/verticalslices/review-performance)<a href="https://agentmods.dev/skills/cratis/verticalslices/review-performance"><img src="https://agentmods.dev/badge/skills/cratis/verticalslices/review-performance.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 | $0.00045 | $0.00596 |
| Opus 5 | $0.00023 | $0.00298 |
| Sonnet 5 | $0.00009 | $0.00119 |
| Haiku 4.5 | $0.00005 | $0.00060 |
Grade A, and why
review-performance 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 5d 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
100% identical to review-performance — 0 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Perform a focused performance review of changed code.
Chronicle / Event Sourcing
- Projections use AutoMap (on by default) — avoids manual mapping cost
- Projections do NOT join on the read model (forces full re-read)
- Reactors do NOT re-query the event log inside
On()— use event data directly - No eager loading of entire event sequences without paging/filtering
- New projections can replay all historical events without crashing
- Events are small — no large blobs or base64-encoded content embedded
MongoDB / Read Models
- Queries filter on indexed fields — no unintentional full-collection scans
- Paged queries use
.Skip()+.Take()— never load all rows - No N+1 pattern — single query returns all needed data
- Read-model records do not embed large nested collections that are never fully iterated
ASP.NET Core / Commands & Queries
- Query endpoints do not hydrate the full collection when only a count is needed
- Command validators are synchronous and in-memory — no I/O in validation
- No
await Task.Run(() => syncWork)wrapping for naturally async work - Response payloads include only fields the client uses — no over-fetching
React / TypeScript
-
DataTableuseslazy+paginatorfor collections larger than ~20 rows - No inline object/array literals passed as props (causes identity change every render)
-
useEffectdependencies are correct — no missing deps, no over-broad deps - Large-collection components wrapped in
React.memoor use stable references - No
JSON.parse(JSON.stringify(x))deep cloning
General .NET
- No LINQ
.ToList()before.Where()— filter before materialising -
IEnumerable<T>not enumerated multiple times — materialise once if needed - Large object logging uses
{@obj}only atDebuglevel
Risk classification
- 🔴 High — measurable degradation at moderate load — must fix before merge
- 🟡 Medium — could degrade under load or at scale
- 🟢 Low — minor inefficiency or style issue
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.
- 5d ago First seen · 56 lines · 45 tokens per session scan A 09b8a20a88cc
review-performance is a skill published in the GitHub repository Cratis/VerticalSlices (2 stars, last pushed 2d ago), licensed MIT. It adds 45 tokens to every session and 596 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to review-performance, differing in 0 lines, and is treated as a copy.
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