Peptul

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that the tool flags mg-versus-mcg mix-ups, that it follows the peptul.com/calculator formula, and that it never recommends a dose—important safety-relevant behavior beyond the raw schema.

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 front-loaded with the core purpose, then gives a clear usage directive and a safety caveat. Every sentence adds value and nothing is redundant or 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?

Although there is no output schema, the description enumerates all returned values: syringe units, volume in mL, concentration, and number of doses. Combined with complete parameter coverage in the schema, an agent has enough context to invoke the tool correctly.

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 the baseline is 3. The description maps the conceptual inputs (vial amount, water added, dose wanted) to the calculation but adds no per-parameter detail beyond what the schema already documents.

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 states a specific verb ('work out how far to draw'), a specific resource (insulin syringe), and the exact inputs/outputs of the calculation. It clearly distinguishes itself from the sibling price/vendor tools, which are unrelated in function.

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 says to use this tool instead of doing arithmetic manually, and clarifies the boundary: it converts an existing dose and never suggests a dose. This gives clear when-to-use and when-not-to-use guidance, even though no sibling alternative exists.

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 provided, the description carries the full burden of behavioral disclosure. It discloses that prices are live, collected nightly, normalized to USD per milligram, and includes both the true cheapest listing and the cheapest from a vendor with an independently verified COA. This is rich behavioral context beyond a simple 'get prices' statement. It doesn't mention rate limits or failure modes, but for a read-only price lookup, the disclosed behavior is substantial.

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 compact and front-loaded: the first sentence states the core function, the second adds key behavioral details, and the third provides examples. Every sentence earns its place, and there is no fluff or repetition of schema fields.

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 read-only tool with no output schema, the description is quite complete. It explains what data is returned (prices per vendor, normalized, with cheapest and verified-cheapest highlights) and the data's freshness. It doesn't specify the exact response format, but without an output schema, that's a minor gap. The example compounds help an agent understand acceptable input values.

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 the schema already documents the 'compound' parameter. The description adds value by giving examples (BPC-157, GHK-Cu, Semaglutide, Retatrutide, TB-500) and clarifying that aliases and slugs are accepted. This goes beyond the schema's generic 'Compound name, alias, or slug' by providing concrete, recognizable instances.

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 function: retrieving live research peptide prices for one compound across all vendors tracked by Peptul, normalized to USD per milligram. It specifies the resource (peptide prices), the scope (all vendors), and the unit normalization, which distinguishes it from generic price tools. It also provides example compounds to anchor the agent's understanding.

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 when to use this tool: when you need current prices for a specific compound across vendors. It doesn't explicitly state when not to use it or name alternatives, but the sibling tools (get_price_history, get_vendor, search_vendors) are contextually distinct. The nightly collection and normalization details give a clear sense of the data's nature, which helps an agent decide if this is the right tool.

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 provided, the description carries the full burden and does well: it discloses nightly recording, the start date (2026-08-27), coverage of every vendor Peptul tracks, and the metric definition (cheapest in-stock price per mg). It does not describe the exact response format or pagination, but the summary statistics are mentioned.

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 compact and front-loaded: the core definition comes first, followed by explicit usage guidance, and ends with an important data caveat. Every sentence earns its place and there is no redundant phrasing.

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 tool with no output schema and no annotations, the description covers the purpose, the key metric, the data source and timeframe, and the distinction from the main sibling tool. The main gap is not spelling out the response shape, but the mention of period low/high/change gives a strong hint.

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 the schema already documents both parameters. The description adds useful interpretive context about what the prices mean, but it does not add new per-parameter semantics beyond what the schema's descriptions already provide.

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 states a specific verb and resource: how a peptide's price has moved over time, with concrete details (cheapest in-stock price per mg each day, period low/high/change). It clearly distinguishes itself from get_compound_prices, which answers current cost, making the tool's purpose 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 explicitly says 'USE THIS when asked whether a price is currently good, whether it has risen or fallen, or what a peptide usually costs'. It also names the sibling alternative, get_compound_prices, and explains the exact division of labor: that tool answers current price, this one answers whether that price is cheap.

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 must disclose behavioral traits. It only describes the data returned (scores, claims, counts) but does not state whether the operation is read-only, what happens on a non-existent vendor (error vs. null), or any side effects. For a get operation, read-only is implied but not confirmed, and error behavior is unaddressed.

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, dense sentence that front-loads the purpose ('One research peptide vendor's public trust record') and enumerates the key data points without redundancy. Every clause earns its place, making it efficient and scannable.

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 (one parameter, no output schema), the description adequately covers the return content by listing the major fields. The only gap is lack of detail on failure behavior (e.g., missing vendor), but for a straightforward get this is a minor omission. The description is largely complete for an agent to call it correctly.

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 schema already fully documents the single parameter 'vendor' with an example ("Certified Peptides"). The description adds no additional meaning or formatting guidance beyond what the schema provides, so a baseline score of 3 is appropriate given high schema coverage.

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 the specific verb 'get' and resource 'vendor record' with a detailed list of contained fields (Peptul Score, COA verification, review counts, issues, shipping, operating status). This clearly differentiates it from siblings like search_vendors (which searches) and get_compound_prices (which is price-focused), making selection 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 implies usage: use this tool when you need a specific vendor's public trust record. It does not explicitly mention when not to use it or name alternatives, but the context of sibling tools and the description's specificity make the intended use reasonably clear. Lacks explicit exclusions or comparison to alternatives.

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 does a good job: it states that only active vendors are returned, lists the returned attributes (Peptul Score, verified-COA status, country), and discloses the ordering ('scored vendors first'). It does not mention potential rate limits, error behavior, or whether query matching is exact or partial, but the key behavioral traits are disclosed.

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 short, purposeful sentences: the first identifies the tool and its scope, the second enumerates the return contents and ordering. No filler or redundancy; it is appropriately sized for the tool's simplicity.

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 simple search tool with no output schema and no annotations, the description adequately explains what is returned and in what order. Minor gaps remain around matching behavior (e.g., substring vs exact match) and the meaning of 'Peptul Score', but the core information an agent needs to call the tool correctly is present.

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%, with both 'limit' and 'query' already described (default and filter semantics). The description adds no additional parameter-level nuance beyond what the schema provides, so the baseline 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 action ('Search') and the specific resource ('Peptul's open research peptide vendor directory'), and describes the output fields returned. It implicitly differentiates from siblings like get_vendor by focusing on directory search, but does not explicitly name the sibling or contrast them.

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 usage: use this tool to search the vendor directory or list top vendors when omitting the query. However, it provides no explicit guidance on when to choose search_vendors over get_vendor, nor any exclusion criteria or alternative routing.

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