Borrowing it
Nothing to install: this file belongs to fulminate-io/knowledge-mcp. 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/fulminate-io/knowledge-mcp/main/.claude/skills/knowledge-tools/SKILL.mdgit clone --depth 1 https://github.com/fulminate-io/knowledge-mcpWrote 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/fulminate-io/knowledge-mcp/knowledge-tools)<a href="https://agentmods.dev/skills/fulminate-io/knowledge-mcp/knowledge-tools"><img src="https://agentmods.dev/badge/skills/fulminate-io/knowledge-mcp/knowledge-tools/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/fulminate-io/knowledge-mcp/knowledge-tools"><img src="https://agentmods.dev/badge/skills/fulminate-io/knowledge-mcp/knowledge-tools.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 | $0.00064 | $0.01986 |
| Opus 5.5 | $0.00026 | $0.00794 |
| Sonnet 5.5 | $0.00013 | $0.00397 |
| Haiku 4.5 | $0.00006 | $0.00199 |
Grade A, and why
knowledge-tools 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 1mo 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
KNOWLEDGE-TOOLS — the graph answers first; the shell is the fallback
Why this rulebook exists
Lanes that live in the shell produce artifacts one step removed from the truth: a citation typed from memory, a caller list from a grep that cannot see interface dispatch, a "does not exist" from one miss, a mechanism asserted without recalling that the graph already recorded it. The graph is indexed, call-graph-aware, and carries every decision, finding and thought from every prior session. Measured lanes that answered code questions with two hundred shell calls and four graph calls delivered the plans that failed audit. The order below is prescriptive, not advisory.
The question-to-call table
Ask the question; make the call named for it; go to the shell only when the table sends you there.
| The question | The call |
|---|---|
| What did prior sessions learn, decide or rule about this? | thoughts({operation:"recall", query:"<topic>"}) then search({graph:"knowledge", queries:[...]}); hydrate hits with query({ids:[...], fields:["summary","content"]}) |
| What was decided, and why? | query({type:"decision", text:"<topic>"}); query({mode:"evidence", id:"<decision>"}) |
| Where is X, what is X named, does anything like X exist? | search({graph:"code", repo:"<repo>", queries:[3 to 5 phrasings]}) |
| Does code SHAPED like this exist, and where? | ast({operation:"match", language:"<lang>", pattern:"<dsl>", where:{...}}); size first with operation:"count" |
| Who calls X; what does X call? | traverse({start:"<id copied from a search or file_symbols hit>", graph:"code", repo:"<repo>", edge_types:["CALLS"], direction:"in"}) plus an ast shape match with include_tests:true. The start id is COPIED from a hit, never composed from a remembered file name; a not found names your id, not the graph, so search the symbol and copy the id it returns |
| What is in this file? | query({mode:"file_symbols", ...}) or file_symbols, then Read the specific range |
| Every site that does X across the tree (a census) | ast({operation:"count"}) then match, package_prefixes to scope, output pasted as the census |
| Every occurrence of an exact literal: a string, a status word, a metadata key, a name | ast({operation:"count", language:"<lang>", pattern:"\"<literal>\""}) then match; a quoted literal is a pattern and matches the literal node wherever it appears, with a by-file count |
| Which files carry a build constraint, or any question about comment text | The shell: grep for the constraint or the comment text, recorded in the census as such. A comment pattern compiles in the DSL but matches no comment node, so this is an allowlisted shell class, not a fallback |
| Which checks cover the shapes I touch? | manage_checks({operation:"run", language:"<lang>", repo:"<abs path>", ids:[...]}); read the hits |
| A structural requirement: a shape that must, or must never, appear | manage_checks({operation:"create", language, name, summary, description, check_type:"ast_pattern", dsl_pattern, check_where, severity, fixture_bad, fixture_good}); admission fires on the bad fixture and stays silent on the good one; then run it over the tree |
| How much did a lane spend, and on which tools? | analyze_usage({operation:"run-detectors", scope:"single", agent:"<lane id>"}) (orchestrator) |
| The idiom or pattern for this mechanism | search({graph:"practice", queries:[...]}); narrow to one origin with source_hub:"<hub id>" |
| The node types and edge types a graph carries | query({mode:"stats", graph:"<family>"}) |
| A plan, ticket or project's shape | query({mode:"plan_tree", id:"..."}) then query({ids:[...], fields:[...]}) for bodies and metadata |
| Why a node is in an unexpected state | query({mode:"examine", id:"..."}) |
| An external API, library or provider behavior | WebSearch / WebFetch the pinned version's documentation, never a remembered shape |
| A uniform structural rewrite across files | ast({operation:"replace", ..., dry_run:true}), read the diff, then dry_run:false |
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.
- 1mo ago Changed fbdf6c3bb504
- 1mo ago First seen · 119 lines · 64 tokens per session scan A 0dcfdcbd155b
knowledge-tools is a skill published in the GitHub repository fulminate-io/knowledge-mcp (1 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 64 tokens to every session and 1,986 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 2026-09-07.
Other skills, from other repositories
knowledge-ingest
Ingest documents, articles, conversations, or supplied text into Knowledge with retained originals, sourced claims, entity updates, source notes, and cross-links; also learn durable lessons from a set of conversations, transcripts, or past sessions (/learn), including the Learn from conversations and Learn from Memory…
mem0-oss-to-platform
Plan, then execute, a migration of a project from the mem0 open-source / self-hosted SDK (local Memory class) to the mem0 Platform / hosted SDK (MemoryClient). TRIGGER when: the developer wants to move, switch, or migrate mem0 off OSS/self-hosted to the hosted API, e.g. "migrate my mem0 setup to the platform", "switch…
forget
Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely…
Cortex
LifeOS memory, prior-session recall, and learning capture. USE WHEN capture this learning, document this learning, what did we learn recently, recent learnings, cortex, knowledge, knowledge base, search knowledge, what do we know about, archive, harvest, knowledge status, develop note, add to knowledge, add a people…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…