Mash Prime

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

With no annotations, the description carries the full burden. It does disclose two real behavioral traits — the sort order ('newest first') and the exact field set returned — which is useful. It omits pagination behavior, result limits, and any auth/visibility constraints for an endpoint that claims to return all posts, so it is only partially transparent.

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?

A single front-loaded sentence with no filler: verb, resource, scope, returned fields, and ordering all in one pass.

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?

No output schema exists, and the description compensates by enumerating the returned fields and their ordering, which is what an agent needs. The only gap for a no-arg list tool is pagination/result-size behavior, which is minor enough to keep this at 4.

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?

The tool takes zero parameters, so there is no parameter semantics to document and the baseline of 4 applies.

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?

States a specific verb (list) and resource (published blog posts) with scope ('all published') and even names the returned fields, so an agent can distinguish it from read_post and search_posts by inference. It stops short of explicitly contrasting itself with those siblings, so it lands at 4 rather than 5.

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 'all published' scope implies this is the enumerate-everything tool as opposed to the filtered search_posts sibling, but the description never says when to prefer it over search_posts or read_post, nor any prerequisites. Usage is inferable rather than stated.

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 and no output schema, the description carries the disclosure burden and does state the return format ('full markdown text') and that it operates on exactly one post. It omits error behavior for an invalid slug and any note on large-post/truncation handling, which keeps it short of a 5.

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?

A single sentence, front-loaded with the action and resource; the parenthetical sourcing hint is compact and earns its place. No filler.

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 one-parameter read tool with no output schema, the description covers identity, scope, return format, and slug sourcing. Minor missing items are invalid-slug behavior and how content is returned when very large.

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 schema already documents 'slug' with a concrete example. The description only restates 'by slug' and adds a sourcing hint, so a baseline 3 is appropriate when the schema does the parameter work.

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?

Specific verb ('Read') plus resource ('full markdown text of one blog post') with scope ('by slug'), and it names the sibling list_posts as the source of slugs. An agent can distinguish it from list_posts and search_posts without opening any schema.

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 gives a clear prerequisite/workflow hint ('get slugs from list_posts'), which tells the agent when to reach for this tool. It does not explicitly contrast with search_posts or state when not to use it, but usage is clear for a single-entity reader.

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 full burden, and it does disclose the ranking basis (embedding similarity) and that results are most-similar-first. It omits failure behavior for an unknown slug, whether results can be empty, and any read-only/pagination context, so meaningful gaps remain.

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 tight sentences: the first front-loads what is returned and the ranking algorithm, the second gives the use case. No filler, no repetition of the tool name.

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 two-parameter, read-only lookup with no output schema, the description covers what is returned and in what order, which is the essential information. It could note emptiness or unknown-slug behavior, but nothing critical to invoking it correctly is missing.

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% and both parameters are documented there, including the limit default and maximum of 5, so the baseline is 3. The description adds nothing about slug format or the significance of the limit cap beyond what the schema already states.

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?

States a specific resource (posts) and mechanism (text-embedding similarity to a given post), plus result ordering. It implicitly distinguishes itself from search_posts by similarity-to-a-post rather than query matching, but never names a sibling, so it stops short of full differentiation.

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?

"Use to follow a thread of ideas from one post to the next" gives one concrete scenario, which is more than nothing. However, it offers no when-not guidance and does not tell the agent when to prefer search_posts or list_posts instead, leaving the routing decision to inference.

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 full behavioral burden. It usefully discloses ranking behavior ('ranked best match first') and the return shape (posts with the most relevant passage as a snippet), but says nothing about result limits, pagination, or empty-result 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?

Two tight sentences with no waste; the core verb and scope come first and the return-format detail follows. Every sentence earns its place.

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 search tool with no output schema and no annotations, the description covers the essentials of what it does and roughly what it returns. It leaves the return structure only loosely specified (no fields, no limits), which is a real but modest gap.

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?

One parameter with 100% schema description coverage, so the schema already documents 'query' fully. The description adds no syntax, format, or query-operator details beyond what the schema provides, making the baseline 3 correct.

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?

States a specific verb (search) and resource (blog posts) with the scope of the search (titles, descriptions, full text). It is clearly distinguishable from read_post and list_posts, though it does not name those siblings explicitly.

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?

No when-to-use guidance, no exclusions, and no routing to alternatives like list_posts or related_posts. The search intent is implied by the verb but nothing states the conditions under which an agent should pick this tool over its siblings.

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 present, the description carries the full burden. It does disclose the return format (markdown, the site's llms.txt) and the breadth of content (every page), which is useful, but it says nothing about read-only safety, response size, or freshness — reasonable inferences for a no-argument info endpoint, but not stated.

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?

One front-loaded sentence that leads with the operative word 'Orientation' and packs the return contents into a compact list. No wasted sentences, though the mid-sentence list is slightly dense and the 'when to use it' clause is ambiguous.

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 zero-argument, read-only informational tool with no output schema, the description tells the agent what it gets back and in what format. That is sufficient to invoke it correctly; only peripheral details like size or caching are absent.

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?

The tool takes no parameters, so the baseline is 4. There is nothing for the description to clarify beyond confirming this is a parameter-free call, which the schema already establishes.

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 names a specific resource (site-level orientation / llms.txt) and states exactly what it returns: who Mash Prime is, what the site covers, and every page as markdown. That is clearly distinct from the content-retrieval siblings (list_posts, read_post, search_posts), though it never names them explicitly.

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?

Usage is only implied: 'Orientation' and the fact that it enumerates every page suggest a first-call/onboarding tool, but there is no explicit when-to-use or when-not-to-use statement, and no alternative is named. Note that 'when to use it' reads as a property of the site's content, not guidance for invoking this tool.

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