/assess

name: assess
license: MIT
compatibility: "Claude Code 2.1.220+. Requires memory MCP server."
description: "Assesses and rates quality 0-10 across multiple dimensions (correctness, maintainability, security, performance, testability, simplicity) with pros/cons analysis. Compares against project conventions and prior decisions from memory. Produces structured evaluation reports with actionable improvement suggestions. Use when evaluating code, designs, architectures, or comparing alternative approaches."
context: fork
# user-typed commands stay interactive; CC >= 2.1.218 backgrounds forks by default (#3093)
background: false
version: 1.8.0
author: OrchestKit
tags: [assessment, evaluation, quality, comparison, pros-cons, rating]
user-invocable: true
allowed-tools: [AskUserQuestion, Read, Write, Grep, Glob, Agent, TaskCreate, TaskUpdate, TaskList, ToolSearch, mcp__memory__search_nodes, Bash]
skills: [code-review-playbook, quality-gates, architecture-decision-record, memory, chain-patterns]
argument-hint: "[code-path-or-topic] [--render=markdown|json-render|both] [--effort=low|medium|high|xhigh]"
complexity: high
persuasion-type: guidance
effort: high
model: sonnet
hooks:
  PreToolUse:
    - matcher: "Read"
      command: "${CLAUDE_PLUGIN_ROOT}/hooks/bin/run-hook.mjs skill/assessment-baseline-loader"
      once: true
metadata:
  category: document-asset-creation
  mcp-server: memory
triggers:
  keywords: [assess, asses, rate, evaluate, grade, score, compare, "how good", "how bad", "red flags", "trade-offs", "pros and cons", "good enough"]
  examples:
    - "rate this code from 0 to 10"
    - "is this approach good enough for production?"
    - "evaluate the trade-offs between Redis vs Postgres"
  anti-triggers: [fix, implement, build, test, commit, review pr, explore]

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

TARGET = "$ARGUMENTS"  # Full argument string, e.g., "backend/app/services/auth.py"
# $ARGUMENTS[0] is the first token (CC 2.1.59 indexed access)

# Model override detection (CC 2.1.72)
MODEL_OVERRIDE = None
for token in "$ARGUMENTS".split():
    if token.startswith("--model="):
        MODEL_OVERRIDE = token.split("=", 1)[1]  # "opus", "sonnet", "haiku", "fable"
        TARGET = TARGET.replace(token, "").strip()

Pass `MODEL_OVERRIDE` to all Agent() calls via `model=MODEL_OVERRIDE` when set. Accepts symbolic names (`opus`, `sonnet`, `haiku`, `fable` on harnesses whose Agent tool lists it; note fable is premium API spend after 2026-07-12) or full IDs (`claude-opus-4-8`) per CC 2.1.74.

> **Switching to Opus via `/model` (CC 2.1.144+):** `/model` now changes the model for the current session only, so picking Opus for an assess run no longer persists past it. Press `d` in the picker only to set a default for new sessions.

Effort detection (CC 2.1.120+)

`${CLAUDE_EFFORT}` is the primary signal. CC 2.1.120 sets this env var from `/effort` or the model picker. `--effort=` token in `$ARGUMENTS` is the explicit override fallback (also covers older CC).

# Read env first (CC 2.1.120+), then check explicit override
EFFORT = os.environ.get("CLAUDE_EFFORT")  # "low" | "medium" | "high" | "xhigh" | None
for token in "$ARGUMENTS".split():
    if token.startswith("--effort="):
        EFFORT = token.split("=", 1)[1]   # explicit override wins
        TARGET = TARGET.replace(token, "").strip()
EFFORT = EFFORT or "high"  # default when CC < 2.1.120 and no flag

Use `EFFORT` to gate dimension count, agent count, and the optional `xhigh` uncertainty pass — see "Effort levels" table above. On CC < 2.1.120 the env var is unset; the explicit `--effort=` override is the only path. `/ork:doctor` Category 14 reports a provably unsupported `xhigh` request.

---

STEP -1: MCP Probe + Resume Check

> Load: `Read("${CLAUDE_PLUGIN_ROOT}/skills/chain-patterns/references/mcp-detection.md")`

# 1. Probe MCP servers (once at skill start)
# memory is alwaysLoad in .mcp.json (CC 2.1.121+, #1541) — probe below kept as fallback for older CC:
ToolSearch(query="select:mcp__memory__search_nodes")

# 2. Store capabilities
Write(".claude/chain/capabilities.json", {
  "memory": probe_memory.found,
  "skill": "assess",
  "timestamp": now()
})

# 3. Check for resume
state = Read(".claude/chain/state.json")  # may not exist
if state.skill == "assess" and state.status == "in_progress":
    last_handoff = Read(f".claude/chain/{state.last_handoff}")

Phase Handoffs

| Phase | Handoff File | Contents | |-------|-------------|----------| | 0 | `00-intent.json` | Dimensions, target, mode | | 1 | `01-baseline.json` | Initial codebase scan results | | 2 | `02-evaluation.json` | Per-dimension scores + evidence | | 3 | `03-report.json` | Final report, grade, recommendations |

---

STEP 0: Verify User Intent with AskUserQuestion

**BEFORE creating tasks**, clarify assessment dimensions:

AskUserQuestion(
  questions=[{
    "question": "What dimensions to assess?",
    "header": "Dimensions",
    "options": [
      {"label": "Full assessment (Recommended)", "description": "All dimensions: quality, maintainabil