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 James-Chahwan/repo-graph --skill glia-overlaygit clone --depth 1 https://github.com/James-Chahwan/repo-graphWrote 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/james-chahwan/repo-graph/glia-overlay)<a href="https://agentmods.dev/skills/james-chahwan/repo-graph/glia-overlay"><img src="https://agentmods.dev/badge/skills/james-chahwan/repo-graph/glia-overlay/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/james-chahwan/repo-graph/glia-overlay"><img src="https://agentmods.dev/badge/skills/james-chahwan/repo-graph/glia-overlay.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 | $0.00099 | $0.08869 |
| Opus 5.5 | $0.00040 | $0.03548 |
| Sonnet 5.5 | $0.00020 | $0.01774 |
| Haiku 4.5 | $0.00010 | $0.00887 |
Grade A, and why
glia-overlay scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
"snippet":{"file":"src/client.ts","start_line":2,"lines":["","export function request(method: string, path: string) {"," return fetch(path, { method });","}",""]}}, How it starts
The opening of the file, as written. The whole thing — 347 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Closing glia's blind spots with the overlay
glia builds its graph from source, so it misses links the source does not spell out: a URL built at runtime, a project's own request / publish / collection helper, an entry point that the OS or a scheduler calls. <repo>/.glia/overlay.toml declares them. glia never calls a model: you write candidate stanzas from the code, and glia measures them. Three commands run the loop:
glia overlay proposelists the gaps a stanza could close. Each gap has a stable id (gap:<16 hex>) and the source lines around it. It writes nothing.glia overlay trybuilds the repo with and without your candidate stanzas and gives each stanza a verdict. It writes only the parse cache.glia overlay acceptis the only writer of.glia/overlay.toml. It adds the stanzas you pick and removes rotted rules by gap id.
The same loop carries architecture rules ([[constraint]] stanzas that glia check enforces): you write the rule, try judges it by the violations glia check finds on the code as it is, and accept writes it.
The schema of every section is in docs/overlay.md (https://github.com/James-Chahwan/glia/blob/main/docs/overlay.md). For queries (where is X, what does X affect), use the glia skill.
From Python. The wheel runs the same three steps in-process, with the same reports as the --json output: glia_py.overlay_propose(repo_paths, categories=None, top_k=20, snippet_lines=3), glia_py.overlay_try(repo_paths, candidate, leave_one_out=True) and glia_py.overlay_accept(repo_path, candidate=None, only=None, remove=None, dry_run=False). repo_paths is a list: the first is the primary repo, whose .glia/overlay.toml the loop reads, and the rest are what --with adds. candidate is the candidate's TOML text, not a path. only and remove are lists of stanza handles and gap ids. A refused candidate, or an accept that would not validate, raises ValueError with the loader's reasons, and nothing is written. overlay_accept is still the only writer of .glia/overlay.toml.
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.
- 5d ago First seen · 347 lines · 99 tokens per session scan A f7a52bbd9ac5
glia-overlay is a skill published in the GitHub repository James-Chahwan/repo-graph (55 stars, last pushed 3d ago), licensed MIT. It adds 99 tokens to every session and 8,869 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-11-02.
glia-overlay compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| glia-overlayJames-Chahwan/repo-graph | Skill | 55 | 3d ago | MIT | A | 99 | Claude Code |
| autoreviewopenclaw/clawhub | Skill | 9.5k | yesterday | MIT | A | 17 | Claude Code, Codex |
| agent-teams-simplify-and-hardenLeoYeAI/openclaw-master-skills | Skill | 2.2k | 6d ago | MIT | A | 115 | Claude Code, Codex |
| omh-code-reviewrlaope/oh-my-hermes | Skill | 5.2k | yesterday | MIT | A | 48 | Claude Code, Codex |
| revdiff-planumputun/revdiff | Skill | 945 | yesterday | MIT | A | 84 | Claude Code |
| explore-unknownsdzhng/skills | Skill | 1.4k | 2d ago | MIT | A | 162 | Claude Code, Codex |
| re0-mergeLilMGenius/paperthin | Skill | 1.4k | 4d ago | MIT | A | 70 | Claude Code |