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 rules/ctxr-dev/llm-wiki-memory/verification-completenessgit clone --depth 1 https://github.com/ctxr-dev/llm-wiki-memoryWhat 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 | $0.00069 | $0.00069 |
| Opus 5 | $0.00034 | $0.00034 |
| Sonnet 5 | $0.00014 | $0.00014 |
| Haiku 4.5 | $0.00007 | $0.00007 |
Grade A, and why
verification-completeness 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 2d 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
Follow the canonical rule (edit that file, never this shadow):
@.agents/rules/verification-completeness.md
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.
- 2d ago First seen · 9 lines · 69 tokens per session scan A faaf511848eb
verification-completeness is a cursor rule published in the GitHub repository ctxr-dev/llm-wiki-memory (129 stars, last pushed 4d ago), licensed MIT. It adds 69 tokens to every session, about $0.0003 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 2026-08-30.
Other cursor rules, from other repositories
memory-reflex
Pensyve memory reflex — the non-optional reasoning discipline for working-memory substrate.
context-loader
Use when starting a new substantive conversation or switching contexts — load relevant memories to prime the session with continuity.
memory-informed-debug
Use when diagnosing bugs, errors, failing tests, or crashes — consult prior debug outcomes and capture root causes in-flight.
memory-informed-longitudinal-work
Long-running multi-session work (research, eval loops, iterative benchmarks) — resume prior lessons, capture per-run outcomes, build up stable truths over time.
session-memory
Use at conversation wrap-up or when the user explicitly indicates end-of-session — capture residual lessons not captured in-flight.
entity-detection
Pensyve entity detection — canonicalization and fallback rules for recall scoping.