Bare Eval

Bare Eval — Isolated Evaluation Calls

Run claude -p --bare for fast, clean eval/grading without plugin overhead.

CC 2.1.81 required. The --bare flag skips hooks, LSP, plugin sync, and skill directory walks.

When to Use

• Grading skill outputs against assertions
• Trigger classification (which skill matches a prompt)
• Description optimization iterations
• Any scripted -p call that doesn't need plugins

When NOT to Use

• Testing skill routing (needs --plugin-dir)
• Testing agent orchestration (needs full plugin context)
• Interactive sessions

Prerequisites

# --bare requires ANTHROPIC_API_KEY (OAuth/keychain disabled)
export ANTHROPIC_API_KEY="sk-ant-..."

# Verify CC version
claude --version  # Must be >= 2.1.81

Quick Reference

| Call Type | Command Pattern | |-----------|----------------| | Grading | claude -p "$prompt" --bare --max-turns 1 --output-format text | | Trigger | claude -p "$prompt" --bare --json-schema "$schema" --output-format json | | Streaming grade | claude -p "$prompt" --bare --max-turns 1 --output-format stream-json | | Optimize | echo "$prompt" \| claude -p --bare --max-turns 1 --output-format text | | Force-skill | claude -p "$prompt" --bare --print --append-system-prompt "$content" | | @-file in prompt | claude -p "grade @fixtures/case-1.md against rubric" --bare (CC 2.1.113 Remote Control autocomplete) |

--output-format stream-json

Newline-delimited JSON events (one per token/tool-call) — lets a runner score partial output or abort early on a failing probe without waiting for the full response.

claude -p "$prompt" --bare --max-turns 1 --output-format stream-json \
  | while IFS= read -r line; do
      # line is a single JSON event; inspect $.type == "content_block_delta"
      jq -r 'select(.type == "content_block_delta") | .delta.text' ` also honors `permissionMode` in `--print` | Permission-gated tools (Bash, Edit) require either `permissionMode: acceptEdits` or explicit allowlists in the agent definition |

Migration test:

```bash
# Run an eval against an agent with a deliberately tight tools: list.
# Graders that previously called Read/Bash freely will now fail unless those
# tools are declared on the agent.
claude -p "$prompt" --bare --print --agent grader-test

If the grader fails with a "tool not permitted" error, add the required tool to the agent's tools: frontmatter and re-run.

CC 2.1.121: CLAUDE_CODE_FORK_SUBAGENT=1 for grader determinism (#1545)

Before CC 2.1.121, the env var only worked in interactive sessions. As of 2.1.121, non-interactive paths (claude -p, SDK) honor it too — each grader invocation gets a fresh forked subagent context.

The cross-eval state-leak problem this fixes:

Without forking, sequential claude -p --bare graders inherit harness state:

| Inherited | Symptom | |---|---| | memory MCP query cache | grader sees stale hit from previous run; same fixture grades differently | | .claude/chain/*.json on disk | grader for "implement" thinks "explore" already ran (file is from previous test) | | ToolSearch deferred-tool cache | first grader's MCP loads bleed into next grader's tool registry | | model picker pref | grader N inherits --model=opus from grader N-1 |

This produced ~5–10% retry rate and non-reproducible scores — the eval baseline drifted between runs, engineers chased phantom regressions.

Fix: tests/evals/scripts/lib/eval-common.sh exports CLAUDE_CODE_FORK_SUBAGENT=1, so every script that sources it (run-trigger-eval, run-quality-eval, run-agent-eval, optimize-description, etc.) gets forked graders automatically. The CI workflow .github/workflows/orchestkit-eval.yml also sets it at the workflow level. Older CC silently ignores the env var (no-op).

Determinism contract: running the same grader on the same fixture twice in a row produces the same score. Verified by tests/evals/scripts/test-grader-determinism.sh.

Performance

| Scenario | Without --bare | With --bare | Savings | |----------|---------------|-------------|---------| | Single grading call | ~3-5s startup | ~0.5-1s | 2-4x | | Trigger (per prompt) | ~3-5s | ~0.5-1s | 2-4x | | Full eval (50 calls) | ~150-250s overhead | ~25-50s | 3-5x |

Rules

Read("${CLAUDE_SKILL_DIR}/rules/_sections.md")

Troubleshooting

Read("${CLAUDE_SKILL_DIR}/references/troubleshooting.md")

Dynamic-workflow harness (template-in-skill)

workflows/skill-fitness.mjs is a runnable dynamic-workflow template — the workflow-backed complement to the static conformance grader (scripts/eval/conformance-check.mjs). It fans out one isolated-context agent per skill to score fitness (freshness / router-clarity / structure) and synthesizes a ranked scorecard, catching qualitative drift a static grep can't (description/body count mismatches, duplicate headings, install-specific absolute paths, version drift). Run it with the Workflow tool:

Workflow({ scriptPath: "${CLAUDE_SKILL_DIR}/workflows/skill-fitness.mjs",
           args: ["assess", "commit", "doctor"] })

Treat it as a template, not a verbatim script — adapt the SKILLS list and rubric per use. Cost is real (~50k tokens/skill; scoring all ~112 is ~6M tokens), so pass an explicit batch via args. Static-first: run conformance-check.mjs (zero tokens) to pre-filter, then this harness for the judgment grep can't make.

Holdout Bake-Off Grading (skill-evolution)

skill-evolution's holdout-promotion gate grades a champion and a challenger SKILL.md over the same sealed holdout via bare-mode forked graders — the canonical consumer of the determinism contract above: identical grader + identical ork-rubric/1.0 + identical sealed set, with CLAUDE_CODE_FORK_SUBAGENT=1 so the only variable is the version under test. Both --bare constraints apply (requires ANTHROPIC_API_KEY, bills tokens directly → on-demand / CI only). See Read("${CLAUDE_PLUGIN_ROOT}/skills/skill-evolution/references/holdout-promotion-gate.md").

Related

• eval:skill npm script — unified skill evaluation runner
• eval:trigger — trigger accuracy testing
• eval:quality — A/B quality comparison
• optimize-description.sh — iterative description improvement
• Version compatibility: doctor/references/version-compatibility.md

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: yonatangross
• Source: yonatangross/orchestkit
• License: MIT
• Homepage: https://orchestkit.yonyon.ai

Install and usage instructions live in the source repository linked above.