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create-task

Create a new Harbor task for evaluating agents. Use when the user wants to scaffold, build, or design a new task, benchmark problem, or eval. Guides through instruction writing, environment setup, verifier design (pytest vs Reward Kit vs custom), and solution scripting.

Quality

91%

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SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

An exceptionally actionable, well-sequenced authoring guide with real validation checkpoints and debugging loops — the verifier-decision and Oracle-verification sections are the standout strengths. The main weakness is structural: everything lives in one long SKILL.md, with the network-policy and multi-step deep-dives inlined instead of split into one-level-deep reference files.

Suggestions

Move the network-policy layer table, flag-merge semantics, and multi-step task.toml schema details into reference files (e.g., references/network-policy.md and references/multi-step.md), keeping a short summary with clearly signaled pointers in SKILL.md.

Trim chatty asides (e.g., 'This is usually where task authors realize something is missing from the Dockerfile') and condense the reward-strategy prose to keep only decision-relevant guidance.

Collect the pinned tool versions (pytest==8.4.1, uv 0.9.7, harbor-rewardkit==0.2.*) into one place or note their maintenance status so time-sensitive details don't drift silently through the doc.

DimensionReasoningScore

Conciseness

Mostly lean and command-dense (exact harbor CLI invocations, complete test.sh scripts, TOML blocks) with no explanations of concepts Claude already knows. A few chatty asides ("This is usually where task authors realize something is missing from the Dockerfile") and pinned versions (pytest==8.4.1, uv 0.9.7, harbor-rewardkit==0.2.*) could be trimmed — anchor 4 rather than 3 (no padded conceptual prose) or 5 (minor trimming genuinely possible).

4 / 5

Actionability

Fully executable, copy-paste-ready guidance throughout: scaffold command with flags, Dockerfile, all three verifier test.sh variants, solve.sh, and complete task.toml examples covering the common cases. Matches the anchor-5 example; anchor 4 would imply gaps in coverage of common cases, which are absent.

5 / 5

Workflow Clarity

Steps 1–9 are clearly sequenced with explicit validation checkpoints and a feedback loop: "Test the environment interactively before writing the solution or tests", and Step 7's "Reward should be 1.0. If it's not, debug in this order" followed by a 4-item ordered debugging checklist. This matches the anchor-5 pattern of explicit validation plus error-recovery guidance.

5 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ absent), so the entire ~480-line body is one monolithic file that inlines reference-grade material — the network-policy layer table and flag-merge semantics (~95 lines) and the multi-step schema details (~120 lines) clearly belong in separate reference files. Section structure is good and external pointers are signaled ("Full reference: docs-mintlify/tasks/network-policies.mdx", "Example task: examples/tasks/hello-multi-step-advanced/"), which lifts it above anchor 2, but the inlined deep-dive content exceeds anchor 4's 'minor organization gaps'.

3 / 5

Total

17

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: third-person voice, explicit 'Use when' trigger clause with natural phrasings, and a concrete enumeration of the skill's four major activities. Its only gap is modest synonym coverage (e.g., 'evaluation', 'grading') in the trigger terms.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions with comprehensive coverage: "Guides through instruction writing, environment setup, verifier design (pytest vs Reward Kit vs custom), and solution scripting" — four concrete action areas matching the anchor-5 example's breadth, with no generic filler that would drop it to 4.

5 / 5

Completeness

Explicitly answers both: what ("Create a new Harbor task for evaluating agents... Guides through instruction writing, environment setup, verifier design...") and when ("Use when the user wants to scaffold, build, or design a new task, benchmark problem, or eval") with concrete trigger phrases, matching the anchor-5 example exactly.

5 / 5

Trigger Term Quality

"scaffold, build, or design a new task, benchmark problem, or eval" gives good natural keyword coverage, but misses common variations users might say such as "evaluation", "grading", or "test". Clearly above anchor 3 (keywords are natural, not just jargon) but not the comprehensive synonym coverage of anchor 5.

4 / 5

Distinctiveness Conflict Risk

"Create a new Harbor task for evaluating agents" carves a clear niche tied to a specific platform with distinct triggers; minimal conflict risk with any generic skill. Anchor 4 would require some overlap with closely related skills, which is not present.

5 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

Arize-ai/phoenix

Path

.agents/skills/create-task/SKILL.md

Reviewed

Table of Contents

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