Scale canary

Scale Canary (Performance & Resource Allocation Audit)

Language: Generate EVERYTHING at runtime in the user's language — questions, answer options, menu labels, recommendations, report narrative. Detect from their messages; never default to English just because this file is English. English is allowed only for technical terms: commands, paths, code identifiers, severity labels (CRITICAL/HIGH/MEDIUM/LOW), and tier names (Light/Standard/Heavy).

Audit code for scalability issues, performance bottlenecks, and resource leaks.

Auditing Categories

1. O(N^2) Complexity — nested loops over growable collections without indexing or caching (crashes at scale).
2. N+1 Database Queries — querying records in a loop instead of a batch JOIN or bulk prefetch.
3. Memory Bloat / Leaks — appending to global arrays/maps without clearing them → unbounded growth.
4. Blocking Main Loop — synchronous FS ops or CPU-heavy work on the main event thread (lag/hangs).
5. Resource Leakage — streams, connections, or handles left open without a finally close.

Per-ORM N+1 shapes, per-stack blocking patterns, and what NOT to flag: read references/checks.md before scanning.

Fix mode (choice-gated)

In Agent Context, after the report, present via ask_question:

• Apply safe optimizations: async-ify synchronous file ops; insert finally blocks for stream closing. Each fix: checkpoint (git stash/commit in a git repo; else copy the file aside — never assume git) → apply → build + tests → auto-revert if newly red.
• Let me pick: user selects specific optimizations.
• Report only: exit unchanged.

Output

| file:line | bottleneck | severity | finding | optimization plan |

Severity: CRITICAL (O(N^2) on user-facing API / unclosed file handles) · HIGH (N+1 query pattern / blocking main loop) · MEDIUM (unbounded cache growth) · LOW (minor efficiency suggestions)

Escalation — Scope & Model Quality

Tiers are capability targets, not platform commands — resolve each to your host's nearest lever. No lever for one? Degrade gracefully — never fake parallelism you can't do; escalate via model tier + reasoning depth instead.

Level	Intent	Capability target	Cost
Light	Spot performance check, hot paths only	Cheapest model · single agent, no sub-agents.	Low
Standard	Balanced scalability audit, multi-category	Balanced model · raised reasoning · sub-agents per category only if your platform runs concurrent workers (else single-agent).	Balanced
Heavy	Full 5-category audit + adversarial profiling verify	Most capable model + largest context · deepest reasoning · max sub-agent fan-out if supported · adversarial cross-check where available.	High

Per-platform Heavy levers + Heavy-run durability: read references/escalation.md before a Heavy run. No concurrent fan-out on your host → escalate by model + reasoning only.

Agent Context (interactive): score the tier rubric, then call ask_question once with the 3 tiers — the pick marked ✓, score shown, labels localized — and wait for the choice before starting. ask_question = your platform's question tool: Claude Code AskUserQuestion · Cline ask_question · Copilot askQuestions · Gemini CLI ask_user (business-tier product; individual tiers ended 2026-06-18 → Antigravity CLI) · Codex request_user_input · Cursor/Devin Desktop (ex-Windsurf)/Antigravity built-in prompts; none → numbered text menu.

Tier rubric (deterministic): +1 each — ① >20 files or whole-repo/cross-module reach ② >2 of this skill's categories relevant ③ release/security/pre-ship context ④ findings will drive code changes. 0–1 Light · 2–3 Standard · 4 Heavy. Freshness cap: scope already audited ≥Standard this session → cap at Light (re-auditing fresh ground wastes tokens; scope to what changed). Default tier: honor .coalmine.json defaultTier unless the user requests a tier for that run — an explicit request overrides everything.

Hook Context (auto-triggered): auto-Light, no tier question, no sub-agents — report first. Interactive session (a user is present) → offer the fix menu after the report; non-interactive → report-only. Never fix without a chosen option.

Entanglement: after the report, if confirmed findings fall in another canary's domain, offer it once via ask_question (one line, max one offer): perf/N+1 → scale-canary · contract/serialization/config → drift-canary · failure-path/retry → resilience-audit · logging/metrics → telemetry-canary · coupling/DI → testability-canary · dependency/CVE → supply-chain-audit · unverified version-sensitive claim → source-grounding · missing/stale rule → gold-standard.

Self error-report: if this skill misbehaves (contradictory instruction, broken procedure, wrong finding class), OFFER to file it at https://github.com/HetCreep/CoalMine/issues/new/choose with a user-reviewed summary — never auto-submit, never include unapproved code or paths.