get_feed_value

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

No annotations provided, so description carries full burden. It discloses reading from live cache updated every cycle, describes return structure (value, computed_at, chain, multi-chain behavior), and explains diagnostic pointers for missing values. This fully informs the agent of behavior.

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 concise yet comprehensive, using clear sections and bullet points. Every sentence adds value without verbosity. Front-loaded with purpose and immediately useful examples.

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?

For a single-parameter tool with an output schema (indicated by context signals), the description covers purpose, usage, parameter format, and return behavior completely. No gaps remain.

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?

With 0% schema description coverage, the description fully compensates by providing explicit examples ('bitcoin_RSI_1H_14', 'pol_EMA_5M_20') and clarifying the 'full feed name' format. This adds significant meaning beyond the schema's simple type and title.

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 clearly states 'Get the latest computed value of a Pythia indicator feed' with a specific verb and resource. It distinguishes from sibling tools like get_market_summary and get_vision_payload by targeting feed values specifically, and contrasts with on-chain usage.

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 explicitly states when off-chain AI agents should use this tool (reasoning about Vision context, choosing Event thresholds, sanity-checking) and provides a clear alternative for on-chain consumers (oracle.request() via get_integration_guide). This is excellent guidance.

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