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apply_cluster_summaries

Persist per-paper summaries generated by an LLM to Obsidian and Zotero. Input a JSON payload matching the expected summarize_cluster output format.

Instructions

Persist a JSON payload of per-paper summaries (when LLM was invoked out-of-band) to Obsidian + Zotero. The payload shape matches the summarize_cluster prompt's expected output: {summaries: [...]}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cluster_slugYes
summaries_jsonYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries full burden. It states the core behavior (persisting to Obsidian+Zotero) and payload shape, but does not disclose side effects, auth needs, or overwrite behavior. Adequate but not comprehensive.

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

Conciseness5/5

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

Two sentences, each adding value. No redundant information. Efficiently communicates purpose and payload constraint.

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

Completeness3/5

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

Output schema exists, so return values are covered. But description lacks details on merge/overwrite behavior, prerequisites, or error handling. Adequate for basic understanding but could be more complete.

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 coverage is 0%, so description must compensate. It clarifies summaries_json as 'payload of per-paper summaries' with shape `{summaries: [...]}`, but provides no additional info for cluster_slug. Partial compensation.

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

Purpose4/5

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

The description uses specific verb 'Persist' and targets 'Obsidian + Zotero', clearly stating what the tool does. However, it does not explicitly differentiate from sibling tools like apply_crystals, leaving some ambiguity.

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

Usage Guidelines3/5

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

The description mentions usage context ('when LLM was invoked out-of-band') and references the summarize_cluster prompt, implying when to use it. But it lacks explicit when-not or alternative tools, so guidance is limited.

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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