Edit strategy (AI edit)

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

With no annotations provided, the description fully discloses behavior: the 300s wait, the verification verdict comparing backtests, return fields including revertToVersion, verdict meanings, and timeout/error handling with jobId. This goes far beyond what annotations would typically provide and gives the agent a comprehensive understanding of side effects and failure modes.

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

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

The description is a single dense paragraph but every sentence earns its place: purpose, parameter guidance, usage tips, return value explanation, verdict definitions, and timeout behavior. It is front-loaded with the core action and progressively details, which is appropriate given the complexity of the tool.

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

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

There is no output schema, so the description must explain return values, and it does thoroughly: a verification verdict with before/after trade counts and return percentages, plus revertToVersion. It also covers all verdict values and the timeout scenario with jobId. For a 2-parameter tool with no annotations, this is complete.

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

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

The schema already covers both parameters fully (100% coverage), so the baseline is 3. The description adds extra value by clarifying where to get strategyId (from list_strategies), suggesting that diagnose_strategy's agentRequest can be pasted verbatim into instruction, and advising to use get_capabilities for valid indicator names. This enrichment pushes it above baseline.

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

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

The description opens with 'Modify an existing strategy with a natural-language instruction using Pyon's AI editor', which is a specific verb+resource pairing. It further lists exact modification targets (entry/exit logic, thresholds, position sizing, symbols) and explicitly ties to fixing issues from diagnose_strategy, clearly distinguishing it from sibling tools like create_strategy or run_backtest.

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

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

The description states when to use the tool ('Use this to change...') and references sibling tools for complementary actions ('Use get_capabilities to check indicator names', 'check with get_job_status'). It does not explicitly list when NOT to use it, but the context is clear enough to guide selection among siblings.

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