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run_snapshot

Run tests and save passing results as the new golden baseline to establish or update expected behavior after intentional changes.

Instructions

Run tests and save passing results as the new golden baseline. Use this to establish or update the expected behavior after an intentional change. Future run_check calls will compare against this snapshot. Call this: (1) after creating a new test with create_test, (2) after confirming a behavioral change is intentional, (3) before making large refactors so you have a clean rollback point. Only passing tests are saved — failing tests are skipped with a warning. IMPORTANT: Automatically detect test_path by looking for a 'tests/evalview/' directory in the current project. If it exists, pass it as test_path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
testNoSnapshot only this specific test by name (optional, snapshots all by default)
judgeNoJudge model for scoring (e.g. 'gpt-5', 'sonnet').
notesNoHuman-readable note about why this snapshot was taken
resetNoDelete all existing baselines before capturing new ones. Default: false.
previewNoShow what would change without saving (dry-run mode). Default: false.
timeoutNoTimeout per test in seconds (default: 30).
variantNoSave as named variant for non-deterministic agents (max 5 per test). E.g. 'v2', 'async-path'.
test_pathNoPath to the test directory. Auto-detect: use 'tests/evalview/' if it exists, otherwise 'tests'.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses that only passing tests are saved (failing tests are skipped with a warning), and it explains the auto-detection of 'test_path'. However, it does not explicitly warn about the destructive nature of the 'reset' parameter, though this is documented in the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and then provides structured usage guidelines. It is about 120 words, efficient but with minor redundancy (e.g., repeating auto-detect from schema). Overall well-organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 8 parameters with full schema descriptions and no output schema, the description integrates well with 'run_check' and 'create_test', covers key behavioral aspects, and provides actionable guidance. It lacks edge-case details but is sufficient for an agent to understand and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description repeats the auto-detection logic for 'test_path' that is already in the schema, but adds no new parameter-specific insights beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Run tests and save passing results as the new golden baseline,' which is a specific verb-resource combination. It distinguishes from sibling 'run_check' by noting that future calls compare against the snapshot, and it lists explicit use cases.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit, numbered usage guidelines: after creating a test, after confirming a change is intentional, and before large refactors. It also contrasts with 'run_check' and mentions prerequisites like having tests created.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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