social-pulse

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

With no annotations, the description carries full burden. It mentions data sources and output fields (first_seen date, sample), which is helpful, but lacks details on update frequency or any side effects.

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, focused paragraph that front-loads the key purpose and includes necessary details without extraneous words.

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 tool's simplicity (2 optional params, no output schema), the description sufficiently covers what the tool does, its data sources, and output format.

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%, and the description echoes the parameters' purpose ('within N days', 'max terms') without adding new semantic detail beyond the schema.

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 defines the tool as returning newly first-appearing terms from specific sources (Reddit/HN newest posts, idea_intel loop), which distinguishes it from sibling tools like trending_topics or mention_pulse.

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 implies its use for early-signal detection of new products, memes, etc., but does not explicitly contrast with siblings or state when not to use it.

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

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

No annotations are provided, so the description carries the full burden. It mentions 'Live data' but does not disclose rate limits, authorization needs, caching behavior, or data freshness beyond that. It adequately describes outputs but lacks potential behavioral caveats.

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 two sentences: first sentence concisely lists capabilities and outputs, second sentence provides usage guidance. No wasted words, key information is front-loaded.

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 tool's complexity (mentions, velocity, sentiment across two platforms), the description covers return values well. No output schema exists, but the description lists outputs explicitly. Lacks differentiation from siblings, but overall is complete enough for an agent to select.

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 description coverage is 100%, so baseline is 3. The description does not add additional parameter-level context beyond what the schema already provides (e.g., days, term, subreddit). It could mention format or constraints but is sufficient.

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 verb (compute) and resource (mentions across Reddit+HN), and lists specific outputs (count, velocity, sentiment). It distinguishes from sibling tools by focusing on tracking a specific term, while siblings like 'emerging_terms' or 'trending_topics' cover broader trends.

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 provides explicit use cases: 'brand-watch, ticker-buzz, product-launch tracking, or trend-confirmation.' It does not mention when not to use or compare to siblings, but the context is clear enough.

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

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

With no annotations, the description carries the burden. It discloses real-time momentum computation, recency-weighted engagement, live data sources, and that results are not stale. No destructive behavior implied.

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 with no wasted words. Front-loaded with attention-grabbing phrasing. Every sentence adds value: purpose, usage, data freshness.

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?

Covers purpose, sources, scoping, and live nature. For a simple tool with no output schema, the description adequately explains what the agent will get (ranked list). Could include a brief example but not necessary.

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%, so baseline is 3. Description adds 'scoped to a subreddit or overall' which overlaps with schema's subreddit param description. No additional semantic detail beyond the schema.

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 returns a ranked list of trending terms/topics from Reddit and Hacker News, with a specific verb ('returns') and resource ('terms/topics'). It distinguishes from sibling tools by specifying sources (Reddit+HN) and real-time momentum.

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?

Explicitly states usage scenarios: 'Use to answer "what's trending on r/<x>" / "what is the internet talking about today"'. Provides clear context for when to use, though no exclusions or alternatives mentioned.

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

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

With no annotations, the description fully describes the tool's behavior: it returns top posts with dominant themes, and each post includes score, comments, sentiment, and a link. It also notes 'Live data,' indicating freshness. This is adequate for a read-only search tool, though it could mention any limitations (e.g., rate limits or authentication). No contradiction with annotations.

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 and front-loaded, with only two sentences that convey the core functionality, use case, and output details. There is no unnecessary information, and every sentence adds value. It is well-structured for an AI agent to quickly understand 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?

Given the tool's moderate complexity and lack of output schema, the description adequately explains what the tool returns: posts with themes, scores, comments, sentiment, and links. It also notes live data. While it does not specify the format of themes or pagination, this is acceptable for a simple list tool.

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?

All four parameters (query, days, limit, subreddit) are described in the schema with clear definitions. The tool description adds no additional meaning beyond what the schema already provides, such as clarifying default values or output behavior. Since schema coverage is 100%, a baseline score of 3 is appropriate.

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's purpose: retrieving top recent posts and dominant discussion themes across Reddit and Hacker News for a query. The verb 'posts' and 'themes' specify the output, and the inclusion of both platforms distinguishes it from typical search tools. While it does not explicitly differentiate from siblings, the purpose is unambiguous.

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 provides a clear usage context: 'Use to quickly understand what are people saying about X.' This directly tells the agent when to invoke the tool. However, it does not specify when not to use it or suggest alternatives from the sibling list (e.g., emerging_terms, trending_topics), which would improve guidance.

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