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 agentmods add skills/sageox/ox/ox-plannpx skills add sageox/ox --skill ox-plangit clone --depth 1 https://github.com/sageox/oxWrote 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/sageox/ox/ox-plan)<a href="https://agentmods.dev/skills/sageox/ox/ox-plan"><img src="https://agentmods.dev/badge/skills/sageox/ox/ox-plan.svg" alt="Measured on agentmods" 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 | $0.00274 | $0.03539 |
| Opus 5 | $0.00137 | $0.01769 |
| Sonnet 5 | $0.00055 | $0.00708 |
| Haiku 4.5 | $0.00027 | $0.00354 |
Grade A, and why
ox-plan 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 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.
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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Whether to render at all is decided by the ox plan JSON (signals.material, guidance) + the user's confirmation / the plan.html config setting — not by this skill. Do not nag on trivial plans; honor the command's signal.
You author the page. ox injects the chrome. For any material plan, author a rich, self-contained interactive HTML page — that page IS the plan of record. ox plan save --file plan.html stores it verbatim in the ledger, derives plan.md from it, and computes the deterministic badges itself. ox plan render --file plan.html serves it with the ox chrome injected (append-only, between <!-- ox-chrome:start/end --> markers — never wrapped, never rewritten). Contract + quality bar: docs/specs/plan-authoring-html.md. Markdown-first remains only the quick path for small, low-stakes plans.
Orchestration (what this skill does)
flowchart TB
RUN["Run ox plan enrich --json on the topic or draft"] --> DET["ox returns DETERMINISTIC badges + context bundle (0 LLM tokens)"]
DET --> READ["AI coworker reads the context bundle: murmurs, sessions, decisions, ADRs, expert artifacts"]
READ --> PAGE["AI coworker authors plan.html: tabs, inspectors, data-driven viz, dark design register"]
READ --> JUDGE["Optional: AI coworker authors JUDGMENT badges, CITED-ONLY (aligns / conflicts / expert-perspective)"]
PAGE --> SAVE["ox plan save --file plan.html (ox derives plan.md + deterministic badges; --annotations optional)"]
JUDGE --> SAVE
SAVE --> GATE{"Render confirmed? (user asked OR plan.html recommend + confirm)"}
GATE -->|"no"| DONE["Saved to ledger; report slug"]
GATE -->|"yes"| RENDER["ox plan render --file plan.html --open (ox injects chrome, opens review loop)"]
-
Get the deterministic signals + context bundle. Run:
ox plan enrich --json --file <plan-file> # or --topic "<subject>" before draftingThis makes no LLM or network call. It returns a
ResultJSON:annotations[]— deterministic, ox-computed badges:collision,prior-art,expert-routing. Each carries{section, kind:"deterministic", type, why, source_url, expert, files}. These are factual — keep them as-is, do not second-guess them. On save, ox computes these itself; you never re-author them.context[]— the pre-retrieved bundle the AI coworker reasons over:{kind: murmur|session|decision|adr|commit|discussion, title, ref, snippet, score, author, when}.signals—{collisions, prior_art, expert_routes, material}.materialis ox's call on whether a render is worth recommending.
-
Author the page (the main event — see "Authoring the page" below). Build the rich, self-contained
plan.htmlthat carries the plan's whole argument: tabbed views, interactive inspectors, data-driven visualizations, the dark design register. -
Optionally author JUDGMENT badges (ox does NO inference). Read the
context[]bundle and produce judgment annotations — additive, passed via--annotations:aligns/conflicts— does the plan agree or clash with a cited ADR, decision, or convention?expert-perspective— the synthesized stance of the area expert.
CITED-ONLY is non-negotiable. Every judgment badge MUST point at a real artifact from the bundle (
ref/source_url): a specific ADR, decision doc, session, commit, or discussion. Rules:- Never invent an opinion, a quote, or a conflict. Precision over recall.
- When the evidence is thin or ambiguous, degrade to a routing nudge —
expert-perspectivebecomes "consult<name>" (naming the expert fromannotations[].expert), NOT a fabricated stance. Putting words in a teammate's mouth is the one failure mode that destroys trust. - When unsure whether a conflict is real, downgrade to "Novel — no prior decision found," not a false
conflicts. - Set
kind:"judgment"on every badge you author so the chrome styles it distinctly from ox's deterministic ones (outlined vs. filled — ox owns that treatment).
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 · 153 lines · 274 tokens per session scan A d3ef61460eac
ox-plan is a skill published in the GitHub repository sageox/ox (51 stars, last pushed today), licensed MIT. It adds 274 tokens to every session and 3,539 once invoked, about $0.0014 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.
Other skills, from other repositories
qmd
Search the vault using QMD semantic search. Use PROACTIVELY before reading files. Preference order: (1) MCP tools — mcpqmdquery, mcpqmdget, mcpqmdmultiget, mcpqmdstatus — if they appear in your tool menu, use them first; (2) CLI qmd --index ... as fallback; (3) Grep/Glob only when QMD is not installed. Trigger…
obsidian-cli
Interact with Obsidian vaults using the Obsidian CLI to read, create, search, and manage notes, tasks, properties, and more. Also supports plugin and theme development with commands to reload plugins, run JavaScript, capture errors, take screenshots, and inspect the DOM. Use when the user asks to interact with their…
unity-vrc-skills-renovator
VRChat skill renovator for knowledge fill, refresh, and quality improvement. Use this skill when updating VRChat skills to new SDK versions, filling missing knowledge, fixing outdated information, or improving skill quality. Targets unity-vrc-udon-sharp and unity-vrc-world-sdk-3 skills. Triggers on: update skills, SDK…
neo4j-snowflake-graph-analytics-skill
Run Neo4j Graph Analytics algorithms (PageRank, Louvain, WCC, Dijkstra, KNN, Node2Vec, FastRP, GraphSAGE) directly inside Snowflake without moving data. Use when running graph algorithms against Snowflake tables via the Neo4j Snowflake Native App ("GDS Snowflake", "graph algorithms in Snowflake", "Neo4j Graph…
neo4j-import-skill
Import structured data into Neo4j — LOAD CSV, CALL IN TRANSACTIONS, neo4j-admin database import full (offline bulk), apoc.load.csv/json, apoc.periodic.iterate, driver batch writes. Covers method selection, header file format, type coercion, null handling, ON ERROR modes, CONCURRENT TRANSACTIONS, pre-import constraint…
neo4j-aura-graph-analytics-skill
Serverless Aura Graph Analytics (AGA) GDS Sessions — covers GdsSessions, AuraGraphDataScience, AuraAPICredentials, DbmsConnectionInfo, SessionMemory, getorcreate, remote graph projection with gds.v2.graph.project and gds.graph.project.remote, gds.v2 session endpoints, gds.v2.graph.construct, AuraDB Cypher API…