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swaroop2005

TraceDelta

by swaroop2005

report_savings

Generate savings reports showing avoided work from capsule reuse, duplicate source queries, and context compression, with labelled token-savings estimates per team over a specified period.

Instructions

Estimated avoided work: capsule reuse, duplicate source queries avoided, source bytes vs response bytes (context compression), and a labelled token-savings estimate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamNo
sinceNo
Behavior2/5

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

No annotations are provided, so the description carries full behavioral burden. The description reads like a list of metrics presented, suggesting a read/report operation, but it doesn't disclose whether this is a mutation, whether it requires prior investigation state, how it computes the estimates, or what the output format looks like. For a tool with zero annotation coverage, this is insufficient behavioral disclosure.

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

Conciseness3/5

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

The description is a compact single sentence listing the report's contents. It's brief and gets to the point, but it's structurally a fragment describing metrics rather than a proper explanation. No waste, but also minimal substance—on the under-specification side rather than the concise-and-complete side.

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

Completeness2/5

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

For a tool with 2 parameters, no output schema, no annotations, and 0% schema coverage, the description should do substantial explanatory work. Instead it lists four metric categories and stops. It doesn't explain the two parameters, what the report format is, when it's meaningful to call it, or what the relationship to sibling tools (find_related_capsules, compare_capsules) is. Given the context richness of sibling names, more is expected.

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

Parameters2/5

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

Schema description coverage is 0% and there are 2 parameters (team, since) with no documentation in the schema. The description doesn't mention either parameter at all, leaving the agent to guess what 'team' and 'since' mean—though they are inferable (team name, time window). With zero schema coverage and no param info in the description, the description fails to compensate.

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

Purpose2/5

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

The description describes what the report contains (avoided work estimates including capsule reuse, duplicate query avoidance, context compression, and token savings), but never states the tool's verb or action clearly. It's unclear whether this tool generates, fetches, or compiles these savings. The name 'report_savings' implies a reporting action, but the description only lists report contents without a clear verb, and doesn't distinguish it from sibling tools like drill_down or verify_claim.

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

Usage Guidelines2/5

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

There is essentially no guidance on when to use this tool versus the siblings. It doesn't say things like 'use after investigation' or 'call to summarize savings.' The semantic content of the savings (capsule reuse, duplicate queries, context compression) gives some implicit context about usage, but there's no explicit when/when-not guidance or mention of alternatives.

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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