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 naimkatiman/continuous-improvement --skill graphgit clone --depth 1 https://github.com/naimkatiman/continuous-improvementWrote 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/naimkatiman/continuous-improvement/graph)<a href="https://agentmods.dev/skills/naimkatiman/continuous-improvement/graph"><img src="https://agentmods.dev/badge/skills/naimkatiman/continuous-improvement/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/naimkatiman/continuous-improvement/graph"><img src="https://agentmods.dev/badge/skills/naimkatiman/continuous-improvement/graph.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 | $0.00019 | $0.01345 |
| Opus 5 | $0.00010 | $0.00673 |
| Sonnet 5 | $0.00004 | $0.00269 |
| Haiku 4.5 | $0.00002 | $0.00135 |
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.
This is a copy
100% identical to graph — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Graph Skill
Run a deterministic orchestration graph from a declarative JSON descriptor.
The runtime consumes the sealed-descriptor and pure-scheduler contracts in
src/graph/* and executes through an independent OS process (omc graph run),
so crash recovery (kill mid-run, rerun, resume from journal) works for real.
Usage
/oh-my-claudecode:graph <descriptor.json>
/oh-my-claudecode:graph "build then test then ask me before deploy" (author the descriptor first)
The execution surface is always the CLI subcommand:
omc graph run <descriptor.json> [--runs-root <dir>]
Run it via the Bash tool for non-interactive graphs. Progress lines stream as
[run], [node], [ok], [fail], [join], [done].
When To Use
- Repeatable multi-step pipelines with explicit dependencies (DAG)
- Work that must survive interruption: kill/restart resumes from journal
- Auditable runs: OCC journal + projection snapshots under
.omc/graph-runs/<run_id>/
When NOT to use: exploratory one-off work (use conversation or /team); anything needing adaptive re-planning mid-run (graphs are deterministic).
Workflow
-
Descriptor given -> go to step 3.
-
Pipeline described -> author the descriptor JSON (schema below), write it next to the project (suggest
.omc/graphs/<name>.json) and show it to the user before running.run_idmust be unique per logical pipeline; rerunning with the samerun_idRESUMES, not restarts. -
Approval nodes: if the descriptor contains any
"kind": "human-approval"node, do NOT run it through the Bash tool (stdin is not interactive there; EOF fails closed to denied). Tell the user to run interactively instead:! omc graph run <file>The
!prefix runs it inside this session with live stdin so y/n works. -
Run and relay progress. Exit codes (normative): 0 succeeded | 1 terminal failed | 19 another writer owns this run (busy) 20 corrupt/tampered journal (fail-closed) | 21 descriptor drift on resume | 70 runtime crash (unmapped error)
-
Resume: rerunning the same command after a crash replays committed transitions and continues. Completed nodes never re-execute.
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.
- 2d ago First seen · 116 lines · 19 tokens per session scan A c0ebe6ddc524
graph is a skill published in the GitHub repository naimkatiman/continuous-improvement (7 stars, last pushed 3d ago), licensed MIT. It adds 19 tokens to every session and 1,345 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to graph, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
opensrc
Fetch dependency source code to give AI agents deeper implementation context. Use when the agent needs to understand how a library works internally, read source code for a package, fetch implementation details for a dependency, or explore how an npm/PyPI/crates.io package is built. Triggers include "fetch source for"…
nopus-configure
Configure nopus complexity sensitivity, extra-simple rewrites, rewrite evidence, and Pi response hiding for this user.
nopus-simplify
Rewrite the immediately preceding assistant response with clearer and more direct prose when the user invokes this skill.
agentpush
Bridge an imported agentpush MCP server (Telegram, WhatsApp, etc.) with live agentproto sessions via the daemon's transmitter subsystem: transmitmessage sends outbound and binds the recipient to a session, inboundwatcherstart polls agentpush for new messages, and inboundendpointcreate/POST /inbound(/:slug) route…
bureau
Drive Bureau — the browser stack's installable capability server: a stealth Firefox (Camofox) + daemon that exposes browser tools as MCP-over-HTTP on :8830, plus a CLI for saved browser identities (sessions), social capture / search, adapter health probes, declarative workflows, and Guilde connection. Use when working…
agentproto-apps
Operate and build Agentproto apps — AIP-42 app bundles (defineApp().emit(dir), APP.md + agents/ + workflows/ + ui/) and their daemon lifecycle (appinstall, appapply, apprun, appstatus, appstop) plus the app-scoped durable data plane (appdataread/write/list/migrate). Covers serving one with a UI (agentproto app serve →…