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 skills add richfrem/agent-plugins-skills --skill rlm-initgit clone --depth 1 https://github.com/richfrem/agent-plugins-skillsWrote 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/richfrem/agent-plugins-skills/rlm-init)<a href="https://agentmods.dev/skills/richfrem/agent-plugins-skills/rlm-init"><img src="https://agentmods.dev/badge/skills/richfrem/agent-plugins-skills/rlm-init/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/skills/richfrem/agent-plugins-skills/rlm-init"><img src="https://agentmods.dev/badge/skills/richfrem/agent-plugins-skills/rlm-init.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 83 uvx/uv tool run commands without ==version create a rug-pull risk.Fix: Pin the version: uvx package-name==1.2.3
- medium MCP Rug Pull · line 86 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00021 | $0.00534 |
| Opus 5.5 | $0.00008 | $0.00214 |
| Sonnet 5.5 | $0.00004 | $0.00107 |
| Haiku 4.5 | $0.00002 | $0.00053 |
Grade A, and why
rlm-init 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 14d 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RLM Cache Initialization (rlm-init)
Initializes a new Recursive Language Model (RLM) semantic cache for zero-dependency high-speed memory.
Contents
Critical Constraints
- Zero-Dependency: Uses standard library Python 3.8+ only; no external databases or daemons required.
- Profile Storage: Profiles default to
.agent/learning/rlm_profiles.json. - Scripted Writes: Never create cache markdown files manually; use
scripts/inject_summary.py.
Quick start
Check existing coverage or initialize a profile:
python3 scripts/inventory.py --profile project
Setup Modes
- Mode A (Standalone): RLM only. Fast keyword lookup across dense file summaries.
- Mode B (RLM + vector-db): RLM keyword pre-filter into vector semantic search.
- Mode C (RLM + obsidian-wiki-engine): RLM as wiki concept distiller.
- Mode D (Super-RAG): Full stack combining RLM, vector store, and wiki concept nodes.
Workflow
- Requirements Discovery: Select target directories, file types, and cache destination.
- Profile Configuration: Define profile entry in
.agent/learning/rlm_profiles.json. - Manifest Creation: Define include/exclude patterns in
<name>_manifest.json. - Audit Gaps: Run
python3 scripts/inventory.py --profile <name>to list uncached files. - Initial Distillation: Deep read and inject summaries via
python3 scripts/inject_summary.py. - Report Readiness: Confirm initialized profile paths and ready state to the user.
Verification
Confirm 100% cache coverage with the inventory script:
python3 scripts/inventory.py --profile project
References
- acceptance-criteria.md — Acceptance criteria for RLM cache bootstrapping.
- rlm-bootstrap-guide.md — Comprehensive bootstrap manual and mode details.
What ships with it
21 files 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.
- assets/resources/distiller_manifest.json 52 B
- assets/resources/manifest-index.json 48 B
- assets/resources/prompts/rlm/rlm_summarize_general.md 71 B
- assets/resources/prompts/rlm/rlm_summarize_tool.md 68 B
- assets/resources/rlm_manifest.json 46 B
- assets/rlm_profiles.json 53 B
- assets/rlm_summary_cache_manifest.json 67 B
- assets/rlm_tools_manifest.json 59 B
- evals/evals.json 693 B
- evals/results.tsv 172 B
- references/acceptance-criteria.md 51 B
- references/cheapest_models.json 40 B
- references/cheapest_models.md 38 B
- references/rlm-bootstrap-guide.md 42 B
- scripts/cleanup_cache.py 33 B runs code
- scripts/distiller.py 29 B runs code
- scripts/inject_summary.py 34 B runs code
- scripts/inventory.py 29 B runs code
- scripts/query_cache.py 31 B runs code
- scripts/rlm_config.py 30 B runs code
- scripts/swarm_run.py 29 B runs code
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.
- 14d ago Changed · -159 lines · -31 tokens per session 3abdd1b7c90a
- 1mo ago First seen · 222 lines · 52 tokens per session scan A 8bd313cd908d
rlm-init is a skill published in the GitHub repository richfrem/agent-plugins-skills (7 stars, last pushed 2d ago), licensed MIT. It adds 21 tokens to every session and 534 once invoked, about $0.0001 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 2026-09-03.
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