Borrowing it
Nothing to install: this file belongs to victoriacity/openakari. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/victoriacity/openakari/main/.claude/skills/orient/SKILL.mdgit clone --depth 1 https://github.com/victoriacity/openakariWrote 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/victoriacity/openakari/orient)<a href="https://agentmods.dev/skills/victoriacity/openakari/orient"><img src="https://agentmods.dev/badge/skills/victoriacity/openakari/orient/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/victoriacity/openakari/orient"><img src="https://agentmods.dev/badge/skills/victoriacity/openakari/orient.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 | $0.00020 | $0.06609 |
| Opus 5.5 | $0.00008 | $0.02644 |
| Sonnet 5.5 | $0.00004 | $0.01322 |
| Haiku 4.5 | $0.00002 | $0.00661 |
Grade A, and why
orient 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 2mo 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 — 346 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/orient
You are starting or resuming a work session on the akari research group repo. Your job is to quickly build situational awareness and recommend the single highest-leverage next action.
Tier selection (ADR 0030)
Orient has two tiers: fast (abbreviated, ~2-3 turns) and full (comprehensive, ~5-7 turns).
/orient fast— run fast orient (skip to "Fast orient" section below)/orient full— run full orient (use the standard procedure below)/orient(no argument) — auto-detect tier:- The scheduler injects
SCHEDULER DIRECTIVE: ... Use /orient fastinto the session prompt when a full orient ran recently (<2h). If you see this directive, run fast orient. Otherwise, run full orient. - If no scheduler directive is present and no explicit argument given, run full orient.
- The scheduler injects
/orient <project-name>— run full orient scoped to that project
Fast orient
When running in fast mode, do only the following:
Step 0: Commit orphaned work
Same as full orient — run !git status, commit and push any orphaned changes.
Gather context (minimal)
Read the following in parallel:
!git log --oneline -5— recent activity!git status(reuse from step 0)projects/*/TASKS.md— for all active projects. Also readprojects/*/README.mdheaders (first ~5 lines) to extract each project'sPriority:field for project-level ranking (ADR 0036). Skip full READMEs, status.md, and roadmap.- Efficiency summary: Read the last 10 work-cycle sessions from
.scheduler/metrics/sessions.jsonlusingReadwith negative offset (e.g., offset=-15) to avoid reading the entire file. Compute and report these concrete metrics (not just flags):- Findings/dollar (primary KPI):
(sum of newExperimentFindings + logEntryFindings) / sum of costUsdacross the 10 sessions. Compare to baseline: 1.29 f/$ overall (from 154 sessions through 2026-02-22). Flag if <0.5 f/$. - Genuine waste rate: Sessions where all
knowledgefields sum to zero AND (orphanedFilesis 0 or absent) ANDfilesChanged < 50ANDbackend != 'cursor'. Report count and %. Flag if >10%. - Orient overhead: Mean
orientTurns / numTurnsfor sessions withnumTurns > 10. Report as %. Baseline: 42% (from 154 sessions). Flag if >40%. - Avg cost/session: Mean
costUsd. Baseline: $3.66. Flag if >$8 (2× baseline). - Avg turns: Mean
numTurns. Flag if >80.
- Findings/dollar (primary KPI):
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.
- 2mo ago First seen · 346 lines · 20 tokens per session scan A a63b53ee1d85
orient is a skill published in the GitHub repository victoriacity/openakari (47 stars, last pushed 7mo ago), licensed MIT. It adds 20 tokens to every session and 6,609 once invoked, about $0.0001 per session on Opus 5.5. 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
orbit-notion
Open Orbit briefing skill — selected by the Orbit pipeline when Notion is the user's only connected connector, or when the user explicitly scopes their daily digest to Notion. Pulls the past 24 hours of document edits, comments, mentions, and database row changes from the user's authenticated Notion connection and…
agentmail
Use your assigned AgentMail inbox to read email tasks, explicitly send or reply, and check delivery. Provided automatically by your inbox assignment.
Cortex
LifeOS memory, prior-session recall, and learning capture. USE WHEN capture this learning, document this learning, what did we learn recently, recent learnings, cortex, knowledge, knowledge base, search knowledge, what do we know about, archive, harvest, knowledge status, develop note, add to knowledge, add a people…
rowboat-spaces
How to work as a member of Rowboat Spaces, the team chat where people and agents work together. Load it once per session, before acting on any request that reaches you from Rowboat; it covers your setup, mentions and hand-offs, the tools, and files.
pinchtab-mcp
Use this skill when a task requires browser automation through PinchTab's MCP server connected to a remote browser instance. Covers navigation, element interaction, data extraction, form filling, multi-step flows, and session management via MCP tools.
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.