graph

A way to query a code graph, a map of files, dependencies, and connections between code elements. It reports structure, callers, dependencies, and the likely blast radius of a change.

In plain words
What is it for?
Use it to find call sites, trace dependencies, inspect repository structure, and assess the impact of changing a function, module, or component.
Why use it?
It helps answer where code is used without reading the whole repository. This makes it easier to estimate which parts may be affected by a change.

Command

Install

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.

agentmods
npx agentmods add commands/jdanigo/hydraia/graph
Clone the repo
git clone --depth 1 https://github.com/jdanigo/hydraia
Per session 13 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 166 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00013 $0.00166
Opus 5 $0.00006 $0.00083
Sonnet 5 $0.00003 $0.00033
Haiku 4.5 $0.00001 $0.00017

Measured 2d ago against content hash 56d78138d10d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

graph 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 2d 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.

commands/graph.md · 11 lines

What it actually says

Query codegraph to answer the following about the current codebase. Prefer graph queries over broad file reads. Report call sites, dependencies, and blast radius concisely.

Query: $ARGUMENTS

When finished, record telemetry for this run: printf 'brief\n' > <base>/.run-complete (where <base> is the artifacts dir resolved at the storage gate — docs/hydraia/ by default, or the external dir if chosen). The Stop hook logs this run's real token/model/sub-agent usage to the local dashboard (delta-scoped per session, so it never double-counts). Do not hand-write the numbers.

Changes

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.

  1. 2d ago First seen · 11 lines · 13 tokens per session scan A 56d78138d10d

Subscribe to this mod's changes

graph is a command published in the GitHub repository jdanigo/hydraia (8 stars, last pushed 12d ago), licensed MIT. It adds 13 tokens to every session and 166 once invoked, about $0.0001 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.