Borrowing it
Nothing to install: this file belongs to 3062-in-zamud/knowledgine. 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/3062-in-zamud/knowledgine/develop/.agents/skills/knowledgine-suggest/SKILL.mdgit clone --depth 1 https://github.com/3062-in-zamud/knowledgineWrote 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/3062-in-zamud/knowledgine/knowledgine-suggest)<a href="https://agentmods.dev/skills/3062-in-zamud/knowledgine/knowledgine-suggest"><img src="https://agentmods.dev/badge/skills/3062-in-zamud/knowledgine/knowledgine-suggest/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/3062-in-zamud/knowledgine/knowledgine-suggest"><img src="https://agentmods.dev/badge/skills/3062-in-zamud/knowledgine/knowledgine-suggest.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 | $0.00067 | $0.00815 |
| Opus 5.5 | $0.00027 | $0.00326 |
| Sonnet 5.5 | $0.00013 | $0.00163 |
| Haiku 4.5 | $0.00007 | $0.00081 |
Grade A, and why
knowledgine-suggest 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.
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
knowledgine-suggest
Purpose
Surface relevant knowledge from the knowledge base based on contextual signals extracted from the current work, rather than a specific search query. Suggest combines search and graph traversal to bring forward knowledge you might not know to search for.
When to Use
- Starting a session — Get context about the area you will work in
- Opening a new file — Discover past knowledge about that component
- Beginning a feature — Find related patterns and past decisions
- Before making changes — Check for warnings or prior art on the topic
- Exploring an unfamiliar module — Find related entities and notes
When NOT to Use
- When you already have a specific query in mind (use knowledgine-recall instead)
- When working on trivial mechanical tasks with no design ambiguity
- After already calling suggest for the same file in the same session
How to Get Suggestions (MCP Tools)
Step 1: Search by context
search_knowledge(
query: string, // Derived from file path, task description, or component name
mode: "hybrid", // Hybrid gives best results for context-based queries
limit: 10
)
Step 2: Find related notes (if you have a note ID or file path)
find_related(
noteId?: string, // ID of a relevant note found in step 1
filePath?: string, // Current file path being worked on
limit?: number, // Max results (default 10)
maxHops?: number // Graph traversal depth (default 2)
)
How to Get Suggestions (CLI Alternative)
knowledgine suggest "<context description>"
knowledgine suggest --file src/commands/setup.ts
Extracting Context
The quality of suggestions depends on the context you provide. Extract signals from:
| Signal | Example |
|---|---|
| Current file path | src/commands/setup.ts |
| Component or class name | SetupCommand, KnowledgeRepository |
| Task description | "add TOML config support to setup command" |
| Feature area | "MCP configuration", "entity extraction" |
| Error message | "TypeError: Cannot set properties of undefined" |
What ships with it
1 file 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.
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 · 94 lines · 67 tokens per session scan A 7acd61397c09
knowledgine-suggest is a skill published in the GitHub repository 3062-in-zamud/knowledgine (3 stars, last pushed 3mo ago), licensed MIT. It adds 67 tokens to every session and 815 once invoked, about $0.0003 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.
knowledgine-suggest compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| knowledgine-suggest3062-in-zamud/knowledgine | Skill | 3 | 3mo ago | MIT | A | 67 | Claude Code, Codex |
| knowledge-ingestopenclaw/openclaw | Skill | 394k | yesterday | MIT | A | 80 | Claude Code, Codex |
| mem0-oss-to-platformmem0ai/mem0 | Skill | 68k | 2d ago | Apache-2.0 | A | 217 | Claude Code, Codex |
| forgetasgeirtj/system_prompts_leaks | Skill | 71k | 2d ago | CC0-1.0 | A | 74 | Claude Code, Codex |
| Cortexdanielmiessler/LifeOS | Skill | 20k | yesterday | MIT | A | 184 | Claude Code |
| memoryopensquilla/opensquilla | Skill | 7.1k | 6d ago | Apache-2.0 | A | 44 | Claude Code, Codex |
| ha-data-storesshiwenwen/hope-agent | Skill | 1.9k | yesterday | MIT | A | 115 | Claude Code, Codex |