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 yogsoth-ai/de-anthropocentric-research-engine --skill repo-dependency-graphgit clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engineWrote 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/yogsoth-ai/de-anthropocentric-research-engine/repo-dependency-graph)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/repo-dependency-graph"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/repo-dependency-graph/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/yogsoth-ai/de-anthropocentric-research-engine/repo-dependency-graph"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/repo-dependency-graph.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00146 | $0.01395 |
| Opus 5 | $0.00073 | $0.00698 |
| Sonnet 5 | $0.00029 | $0.00279 |
| Haiku 4.5 | $0.00015 | $0.00139 |
Grade A, and why
repo-dependency-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 11d 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
repo-dependency-graph
Turn a skill repo (or a whole campaign package) into a clean, interactive
use-dependency graph: read the original SKILL.md + design docs, reconstruct
the real use edges, and render one offline HTML per repo that looks and behaves
like an Obsidian graph (force-directed, draggable, neighbourhood-highlight, HTML
hover tooltips).
This skill exists because a repo's frontmatter alone gives a broken graph — real
routing lives in prose, in references/*-index.md, and in same-layer escalation
handoffs. Reconstructing the true graph takes a careful read of each repo, then a
deterministic render. This skill captures both halves so the result is consistent
every time and reusable across all repos.
The model (read references/layer-rules.md for the full rules)
- 5 vertex types:
campaign(red) ·strategy(cyan) ·tactic(yellow) ·sop(purple) ·references(gray dashed, = a.py/.mdhelper file). - One edge type
use:A -->|use| B= A invokes/orchestrates B (caller → callee). - Layer comes from frontmatter
type:/layer:(NOTexecution:). Infer from body+README only if absent, and record the reasoning. - Escalation = same-layer
sop → sopuse edge (locked decision): "escalate to X" / "for deeper analysis use X" / "import X" are all drawn asuseedges. Do NOT promote a skill's layer just to make the edge look legal — same-layer handoff is a first-class edge here.
Workflow
1. Read the repo and reconstruct the dependencies
For each skills/*/SKILL.md: read the full body + frontmatter (layer field,
and any prose that invokes/escalates to another skill or points at a
references/ helper). Also read README.md, docs/, assets/, and any
*-index.md — real routing often lives there, not in frontmatter.
Only draw an edge the design files actually justify. If two skills are
independent siblings, leave them unconnected — do not invent edges. A pointer to
an external MCP tool (alphaxiv, brave) is a tool, not a vertex. A broken /
never-used file pointer does not justify a references vertex — verify the live
reference.
What ships with it
4 files 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.
- 11d ago First seen · 113 lines · 146 tokens per session scan A 06699d3d4c7b
repo-dependency-graph is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (456 stars, last pushed yesterday), licensed Apache-2.0. It adds 146 tokens to every session and 1,395 once invoked, about $0.0007 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 2026-08-30.
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