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 strikersam/autonomous-ai-agency --skill graphifygit clone --depth 1 https://github.com/strikersam/autonomous-ai-agencyWrote 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/strikersam/autonomous-ai-agency/graphify)<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/graphify"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/graphify/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/strikersam/autonomous-ai-agency/graphify"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/graphify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Agent Snooping · line 17 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00056 | $0.01572 |
| Opus 5 | $0.00028 | $0.00786 |
| Sonnet 5 | $0.00011 | $0.00314 |
| Haiku 4.5 | $0.00006 | $0.00157 |
Grade A, and why
graphify 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 12d 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: graphify — Knowledge Graph Token Optimization
Why This Exists
Reading raw source files to understand context is expensive. On a codebase this
size, a single "understand the auth flow" task can consume 8–20k tokens just in
file reads. Graphify pre-processes every file into a structured knowledge graph
(graph.json) using local AST parsing (no API calls for code). Claude queries
the graph instead of reading files — the upstream benchmark shows 71.5x fewer
tokens per query on large mixed corpora.
Installation (one-time per machine)
# Install the CLI
pip install graphifyy # PyPI name uses double-y; CLI stays `graphify`
# macOS managed envs: use pipx install graphifyy instead
# Install the /graphify slash command into Claude Code
graphify install
# Build the initial graph for this repo
cd /path/to/local-llm-server
graphify .
On success you'll have:
graphify-out/graph.json ← local queryable graph (gitignored; path-specific IDs)
graphify-out/graph.html ← interactive visualization (gitignored, >5k nodes skipped)
graphify-out/GRAPH_REPORT.md ← god nodes, surprising edges, suggested questions
graphify-out/cache/ ← SHA256 change-detection cache (gitignored)
Session-Start Auto-Refresh
settings.json in this repo configures a SessionStart hook that runs
.claude/hooks/graphify-refresh --session when any Claude Code session opens. The wrapper runs graphify update . without unsupported flags, then prints the committed report summary. This keeps the graph current without full rebuilds — only changed files are re-processed.
The hook prints a one-line status so Claude knows the graph state:
=== GRAPHIFY KNOWLEDGE GRAPH (auto-loaded) ===→ report summary loaded; query graph.json[graphify] not installed→ install withpython -m pip install graphifyyand retry
How to Use the Graph (Token Savings Protocol)
Instead of reading raw files:
# EXPENSIVE (reads 300-line file = ~1200 tokens)
/graphify explain "How does ModelRouter select a model?"
# Returns a targeted 200-token answer from the pre-built graph
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.
- 12d ago First seen · 142 lines · 56 tokens per session scan A e2a785c3d75e
graphify is a skill published in the GitHub repository strikersam/autonomous-ai-agency (8 stars, last pushed today), licensed MIT. It adds 56 tokens to every session and 1,572 once invoked, 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 2026-08-31.
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