assess

assess is a command for coding agents from yonatangross/orchestkit. It costs 72 tokens per session (5,985 once invoked), scanned A, original, MIT.

A code-quality assessment command that rates work from 0 to 10 across correctness, maintainability, security, performance, testability, and simplicity. It also compares the work with project conventions and earlier decisions.

In plain words
What is it for?
Use it to assess files, services, components, caching plans, database designs, or other implementation choices and receive pros, cons, scores, and recommendations.
Why use it?
It gives a structured review of code or a technical decision, making weaknesses and possible improvements easier to identify.

Command

Part of the ork plugin — 35 commands, 15 agents shipped together

Install

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.

agentmods
npx agentmods add commands/yonatangross/orchestkit/assess
Clone the repo
git clone --depth 1 https://github.com/yonatangross/orchestkit

Or install ork, the plugin that ships this one along with the rest of its 35 commands, 15 agents.

Wrote 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.

agentmods badge for assess

README.md
[![agentmods](https://agentmods.dev/badge/commands/yonatangross/orchestkit/assess.svg)](https://agentmods.dev/commands/yonatangross/orchestkit/assess)
Your own site
<a href="https://agentmods.dev/commands/yonatangross/orchestkit/assess"><img src="https://agentmods.dev/badge/commands/yonatangross/orchestkit/assess.svg" alt="Measured on agentmods" height="20"></a>
Per session 72 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,985 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00072 $0.05985
Opus 5 $0.00036 $0.02993
Sonnet 5 $0.00014 $0.01197
Haiku 4.5 $0.00007 $0.00598

Measured 3d ago against content hash 6fadd5b3f9cb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

assess 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 3d 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.

plugins/ork/.cursor-plugin/commands/assess.md · 453 lines

How it starts

The opening of the file, as written. The whole thing — 453 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Auto-generated from skills/assess/SKILL.md

Source: https://github.com/yonatangross/orchestkit

Assess

Comprehensive assessment skill for answering "is this good?" with structured evaluation, scoring, and actionable recommendations.

🎯 Quick Start

/ork:assess backend/app/services/auth.py
/ork:assess our caching strategy
/ork:assess --model=opus the current database schema
/ork:assess frontend/src/components/Dashboard

Effort levels (CC 2.1.111+ adds xhigh)

Effort Behavior
low / medium Subset of dimensions, faster turnaround
high (default) All six dimensions with pros/cons
xhigh All six dimensions + one additional assessor pass focused on uncertainty/caveats; emits confidence per dimension

xhigh silently falls back to high on a model that does not implement it: no error, no log line. /ork:doctor Category 14 reports this, and only when it can positively prove the active model lacks the tier.

Argument Resolution

Step 0: resolve a conversational reference first

$ARGUMENTS is often not a path. For a bare pronoun or deictic (them, this, that, these, they, same, the above, the last one, what we just did) or an empty target after flags are stripped, the subject is in the conversation. Read back for the NEAREST concrete one (a file just discussed, a diff or PR just opened, a component just investigated) and announce the resolution in one line, so a wrong guess costs a correction rather than a turn: "Reading 'them' as the 3 pretool guards we just probed; say otherwise and I'll switch."

Refusing is the bug, not the safe option. Asking "what does this refer to?" when the previous turn named the subject burns a round-trip re-deriving what is already on screen. Measured 2026-08-28: the operator sent /ork:assess them throguhly one message after "bug in orchestkit hooks", mid-investigation of pretool/bash/dangerous-command-blocker, and this skill replied that "them" had "no antecedent anywhere in this conversation". It had two.

Read the full file on GitHub · 453 lines

Changes

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.

  1. 3d ago First seen · 453 lines · 72 tokens per session scan A 6fadd5b3f9cb

Subscribe to this mod's changes

assess is a command published in the GitHub repository yonatangross/orchestkit (225 stars, last pushed today), licensed MIT. It adds 72 tokens to every session and 5,985 once invoked, about $0.0004 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.