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 skills/yasinyaman/graphlore/graphlore-explorenpx skills add yasinyaman/graphlore --skill graphlore-exploregit clone --depth 1 https://github.com/yasinyaman/graphloreWhat 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 | $0.00093 | $0.01722 |
| Opus 5 | $0.00046 | $0.00861 |
| Sonnet 5 | $0.00019 | $0.00344 |
| Haiku 4.5 | $0.00009 | $0.00172 |
Grade A, and why
graphlore-explore 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 yesterday.
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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Exploring a codebase with Graphify
The graphlore MCP server (tools are named graphlore_*; they read the
Graphify-built graph) exposes a codebase knowledge
graph as tools. Reach for it before grepping or reading many files: it
answers structural questions ("what connects to X", "which subsystems exist",
"where does this flow run") cheaply, returning just the relevant slice instead
of whole files.
If the graphlore_* tools are not available, the MCP server isn't connected — see
the project README for the .mcp.json / Claude Desktop config.
The server reads one project — the directory it was started with; there is no
per-call project argument, so a question about another repo needs another server.
graphlore_build requires the graphify CLI on PATH: graphlore has no extractor
of its own.
Preconditions: make sure the graph exists and is fresh
graphlore_freshness()— isgraph.jsonstale vs. the current git HEAD?- If missing or stale:
graphlore_build(".", update=True)(AST-only update needs no API key;mode="deep"adds semantic edges but needs a backend key).
Find code by what it does — graphlore_locate
For a behavioral question ("where is retry/backoff handled?", "how are redirects
followed?"), reach for graphlore_locate("<natural-language question>") first: one
call runs semantic search, maps the top hit to its enclosing graph node, and
returns the token-budgeted subgraph around it plus hidden_links — semantically
similar code that is structurally disconnected (duplication / missing-abstraction /
sync-async-twin candidates that neither search nor the graph surfaces alone). Works
across Python, JS/TS, Go, Java, Rust, C++ and 165+ languages. Needs the optional
[semble] extra; without it, fall back to graphlore_search (name-based) and the
structural flow below.
Canonical flow (cheap → targeted)
graphlore_overview()— ALWAYS first. Size, god nodes, community count, surprise edges, and suggested next steps.graphlore_communities()— the major subsystems. Read these like a table of contents.graphlore_subgraph("<node>", hops=2, budget_tokens=1500)— the workhorse. A token-budgeted BFS slice around a node; this is the cheap way to feed the model just the relevant structure. Start from a god node or a community member.graphlore_query("<natural-language question>", budget=1500)— ask the graph directly (BFS/DFS traversal, no LLM key needed).graphlore_node_details("<node>")— resolve a node to itsfile:line, type, community, and docstring when you need to jump to source.
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.
- yesterday First seen · 118 lines · 93 tokens per session scan A c9ebf588aed9
graphlore-explore is a skill published in the GitHub repository yasinyaman/graphlore (2 stars, last pushed 3d ago), licensed MIT. It adds 93 tokens to every session and 1,722 once invoked, about $0.0005 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 2026-08-31.
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