Get the Probability of Success estimate for a node, including the base rate, adjustment factors with reasoning, confidence interval, and model version.
Returns None for nodes without a PoS score (typically only late-stage pipeline drugs are scored).
| Name | Required | Description | Default |
|---|---|---|---|
| node_id | Yes | Node identifier |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description fully discloses the return value details (components of PoS) and the None case. It provides transparency about what the tool does beyond a simple read operation.
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?
Two sentences, no redundant information. Every part adds value: first sentence states purpose and output contents, second covers the edge case.
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?
Given the single required parameter and existing output schema, the description covers the tool's behavior sufficiently. It could mention the expected node type, but it's adequate for selection and invocation.
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?
Schema coverage is 100% for node_id, and the description adds no additional semantic information about the parameter. The baseline of 3 is appropriate as the schema already describes the parameter.
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 the tool retrieves the Probability of Success estimate for a node, listing specific components (base rate, adjustment factors, etc.) and mentioning when it returns None. This distinguishes it from sibling tools like 'get_node' or 'get_writeup'.
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?
It explicitly notes that nodes without a PoS score return None, typically for early-stage drugs, implying when the tool is not useful. No explicit alternatives are given, but the context is clear.
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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Tools have mostly distinct purposes, though get_node and get_pos_score both provide probability-of-success data (get_node includes a summary, get_pos_score gives detailed factors). Descriptions clarify the difference, so confusion is minimal.
Naming follows a verb_noun pattern but mixes verbs: 'find', 'get', 'list', 'search'. Within the 'get' group, all are consistent. The mix is not chaotic and remains predictable.
13 tools cover the biomedical domain well without being excessive. Each tool has a clear purpose, from searching and listing to fetching detailed node data, statistics, and specialized reports.
For a read-only database, the tool set is complete. It supports search, filtered queries, detailed node retrieval, specialized data (PoS, freshness, staleness), and statistics. No obvious gaps for typical query needs.