Borrowing it
Nothing to install: this file belongs to spideynolove/memory. 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/spideynolove/memory/main/.claude/commands/analyze.mdgit clone --depth 1 https://github.com/spideynolove/memoryWrote 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/commands/spideynolove/memory/analyze)<a href="https://agentmods.dev/commands/spideynolove/memory/analyze"><img src="https://agentmods.dev/badge/commands/spideynolove/memory/analyze/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/commands/spideynolove/memory/analyze"><img src="https://agentmods.dev/badge/commands/spideynolove/memory/analyze.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 | $0.00009 | $0.00372 |
| Opus 5.5 | $0.00004 | $0.00149 |
| Sonnet 5.5 | $0.00002 | $0.00074 |
| Haiku 4.5 | $0.00001 | $0.00037 |
Grade A, and why
analyze 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 2mo 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
Correction Analysis
Compare before/after code content against stored rules to detect rule violations and track repeated mistakes.
When to Use
Run immediately after the user corrects your work:
- User says "no", "wrong", "not that" followed by the fix
- User edits your code and shows the corrected version
- User provides feedback that reveals a missed rule
Usage
analyze_corrections(
before_content="[original code that was wrong]",
after_content="[corrected code]"
)
What It Does
- Extracts all stored rules from memory (memory_type = "rule")
- Analyzes before_content for rule violations using trigger keywords
- Checks if after_content fixes those violations
- Logs violations to rule_violations table with frequency tracking
- Returns JSON with detected violations
Output Format
{
"status": "violations_found" | "no_violations",
"count": 3,
"violations": [
{
"rule_id": "abc123",
"rule_trigger": "before adding features",
"violation_id": "viol_xxx"
}
]
}
Related Tools
get_rule_violations()— View all tracked violationsresolve_rule_violation(violation_id)— Mark a violation as resolved/correct— Review active violations before starting work
Pattern
This implements the correction cycle from claude-memory-engine:
- User corrects you → run
/analyzeto log the mistake - Before next task → violations auto-load as reminder
- Same mistake 3+ times → consider upgrading to a hard rule
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.
- 2mo ago First seen · 61 lines · 9 tokens per session scan A b233872122c8
analyze is a command published in the GitHub repository spideynolove/memory (3 stars, last pushed 7mo ago), licensed MIT. It adds 9 tokens to every session and 372 once invoked, about $0.0000 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 2026-08-31.
Other commands, from other repositories
is-not-duplicated
please investigate the codebase based on your changes - do we have code duplication? After analysis, write updates to DUPLICATIONREPORT.md with the results. Keep in mind that other agents could keep their records, so you need to check the document first, decided to update or add new information.
review
Make a review quiz page from what is due and what you just learned.
review
Comprehensive code review for blz changes.
review
Review the current plan with peer LLMs via inspectrum.
inventory
Codebase inventory skill — scans the repo for a named pattern (inline SQL, fetch calls, feature flags, debug leftovers, deprecated APIs, etc.) and emits a structured Markdown inventory cross-referenced with framework metadata (routes, handlers). Language-agnostic and pack-driven — the engine matches whatever a YAML…
implement
Multi-agent advisory squad workflow for implementing code changes: classify → score risk → select agents → planner → Gate 1 (plan approval) → advisory squad → Gate 2 (Blocker halt) → implementer → consolidator → verdict. Auto-detects depth (quick/normal/deep) from risk + file count; pass --quick or --deep to override.…