Instapdown Instagram Toolkit

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

No annotations provided, so description carries full burden. It mentions 'public Instagram creator' implying access restrictions but does not disclose rate limits, authentication needs, error handling, or what happens if the account is private or has fewer than 12 posts.

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 fluff. First sentence defines the action, second provides context. Every word is necessary.

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 no output schema and no annotations, the description explains input (username of public creator) and output scope (last 12 posts, ranked by frequency). It is fairly complete for a simple tool, though output format could be mentioned.

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% for the single parameter (username) with description 'Public Instagram username'. The tool description does not add additional meaning beyond matching that, so baseline 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 extracts hashtags from a creator's last 12 posts and ranks them by frequency. The verb 'extract' and resource 'hashtag set' are specific. It distinguishes from sibling tools like search_hashtags and get_hashtag_niche.

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 for analyzing a creator's hashtag strategy ('reveals someone's actual working tag stack') but does not explicitly state when to use vs alternatives like search_hashtags or get_hashtag_niche. No exclusions or when-not-to-use guidance.

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 provided, so description carries full burden. It discloses that it downloads all slides (photos and videos) and returns URLs in order. However, it omits details like authentication needs, rate limits, or behavior for private posts. Adequate but could be more informative.

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, front-loaded with the main action, no fluff. Every sentence adds value. Ideal conciseness.

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 tool with one parameter and no output schema, the description covers purpose, input type, and return value. It mentions 'public' but could note authentication or error conditions. Nearly complete.

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 the description restates 'Public Instagram carousel post URL' from the schema. It adds no extra meaning beyond the schema, so baseline 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 'Download every slide of a public Instagram carousel post' with specific verb (download) and resource (carousel post). It distinguishes from sibling tools like download_photo (single photo) and download_video (single video) by explicitly mentioning carousel and multiple slides.

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 for carousel posts but does not explicitly say 'use this when the post is a carousel' or provide alternatives. It is clear in context but lacks explicit exclusion of other tools.

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 provided, so description carries full burden. Describes core behavior but omits details like authentication needs, rate limits, error handling, or output format.

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, no fluff, directly conveys essential information. Efficient and well-structured.

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 low complexity (1 param, no output schema), description is mostly complete but lacks details about the output (e.g., returns image data or a URL) and any prerequisites or side effects.

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% for the single parameter 'url'. Description repeats the schema description, adding no new semantic meaning beyond what schema already provides.

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?

Description clearly states verb 'download', resource 'single-image Instagram post', and detail 'original full resolution'. It also distinguishes from sibling 'download_carousel'.

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 advises to use 'download_carousel' for posts with multiple slides, providing clear guidance on when not to use this 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?

No annotations provided, so description must cover behavior. Mentions 'full-resolution', '~1080x1080 JPG', and 'straight from CDN', offering some detail. However, lacks disclosure on rate limits, error handling for non-existent accounts, 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?

Two sentences, no wasted words. Concise and immediately informative.

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 basic purpose and parameter, but given no output schema and multiple sibling tools, could benefit from specifying return type, error scenarios (e.g., private accounts), or differentiation from other download tools.

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?

Only one parameter with schema description 'Public Instagram username'. The tool description adds 'for any public Instagram account', clarifying the constraint beyond the schema. With 100% schema coverage, the description adds meaningful context.

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?

Description clearly states 'Download the full-resolution profile picture for any public Instagram account.' Verb (download) and resource (profile picture) are specific. Distinguishes from sibling download tools that target other media types.

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?

Implied usage for public accounts, but no explicit guidance on when not to use this tool versus alternatives like download_photo or download_video. No exclusions or context provided.

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 provided, so the description carries full burden. It discloses that the output is original 9:16 HD MP4 URL and audio, no watermark, no re-encoding, and the error case for private accounts.

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?

Three sentences, front-loaded with the action, no redundant information. Every sentence adds value.

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 (1 param, no output schema, no annotations), the description covers purpose, output, constraints, and error condition. Lacks details on rate limits or auth, but adequate for the task.

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?

With 100% schema coverage, baseline is 3. The description adds context that the URL must be from a public post, but schema already says 'Public Instagram Reel URL'. No additional parameter meaning beyond 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 downloads an Instagram Reel from a public URL, specifying the output format (HD MP4, audio track, no watermark). It distinguishes from sibling tools like download_video and extract_reel_audio by focusing on reels with original quality.

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 condition: only public accounts work; private accounts return HTTP 422. However, it does not explicitly compare to sibling tools or state when to use this over 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 provided, the description carries full burden. It clearly states behavioral traits: fetches only currently-active stories, 24-hour window, returns MP4/JPG URLs, and errors on private accounts. This is thorough and avoids surprises.

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, front-loaded with the key action and result. Every word adds value: specifies active stories, timeframe, output formats, and error case. No redundancy 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?

Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is fully complete. It explains input, output format, temporal constraints, and error handling for private accounts. Nothing is left unclear.

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%, providing baseline 3. The description adds valuable context beyond the schema by specifying 'currently-active' and 'within the 24-hour visibility window', clarifying the temporal constraint on the username parameter.

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 uses specific verbs ('Fetch', 'Returns') and clearly states the resource ('currently-active Instagram Story') and scope ('public username within 24-hour visibility window'). It distinguishes from sibling tools like download_reels and download_photo by focusing specifically on active stories.

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 explains when to use (to get active stories for a public username) and notes a failure condition (private accounts return HTTP 422). However, it does not provide explicit guidance on when not to use this tool or mention alternatives among siblings, such as download_reels for video content.

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 full burden. It discloses that the tool returns original MP4 with no re-encoding, which is helpful. However, it does not mention potential failure scenarios (e.g., private URL, invalid URL) or any authentication requirements.

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, front-loaded with the primary action. Every word adds value; no redundant or verbose language.

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 sufficiently covers purpose, input, and output. Explains that it returns original MP4, which compensates for the lack of an output schema.

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% with a single parameter. The description reiterates that the URL must be a 'public Instagram video post URL', adding minimal value beyond the schema's description. No additional format or validation details are provided.

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?

Clearly states the tool downloads an Instagram feed video (not a Reel) from a public post URL and returns the original MP4. The verb 'download' and resource 'Instagram feed video' are specific, and the distinction from Reels helps differentiate from sibling tools.

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 'not a Reel', providing a clear exclusion. Implies the alternative sibling tool download_reels for Reels. However, it doesn't explicitly mention when not to use (e.g., private URLs) or other contextual prerequisites.

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 exist, so the description must disclose behavioral traits. It mentions calculation and outputs but does not discuss side effects, authentication needs, rate limits, or whether the tool is read-only. For a computation tool, the lack of destructive hint is acceptable but could be clearer.

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?

Three sentences with no redundancy. The first sentence states purpose and methodology, second sentence lists inputs, third sentence lists outputs. Concise and well-structured.

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?

The description covers purpose, inputs, and high-level outputs. However, since there is no output schema, it could specify the types (e.g., numeric ER, string rating) or structure. Still, for a simple calculator, it is fairly complete.

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 adds context about weighted signals but does not specify weights or formula beyond what the schema parameter descriptions already provide (e.g., average per post, optional default 0). Minimal added value.

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 calculates a weighted Instagram engagement rate using 2026 Reels-ranker signals (likes, comments, saves, shares) and returns weighted ER, follower-tier benchmark, and performance rating. It distinguishes from sibling tools that focus on downloads or hashtags.

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 context (calculating engagement for Instagram) but provides no explicit guidance on when to use this tool versus alternatives like engagement_health_check or get_best_time_to_post. No exclusions or when-not-to-use notes.

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?

The description covers actions and outputs but omits behavioral traits such as rate limits, authentication requirements, or response format. With no annotations, it carries the full burden but leaves gaps.

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, informative sentence with no extraneous words, efficiently conveying purpose and key outputs.

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 simple input (one parameter) and no output schema, the description covers all necessary information: what data is pulled (last 12 posts) and what is returned (rates and comparisons), making it complete for the tool's complexity.

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 provides 100% coverage for the single parameter 'username' with a clear description. The tool description adds context about what the tool does but does not enhance parameter semantics 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 audits engagement health of a public Instagram profile, specifying the actions (pulls last 12 posts) and outputs (engagement rate, save rate, etc.), distinguishing it from sibling tools like engagement_calculator.

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 implies the tool is for auditing engagement but does not specify when to use vs alternatives, nor provide any exclusions or prerequisites. The presence of sibling tools with overlapping functions suggests a need for clearer guidance.

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 carry the full burden. It states the action (extract) and output (URL), but does not disclose potential side effects, rate limits, or requirements beyond 'public'. The read-like nature is implied but not explicit.

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 with no fluff: first sentence defines the action and output, second sentence gives use cases. Every word 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 simple tool with one parameter and no output schema, the description covers the core functionality and use case. However, it lacks details on error conditions (e.g., non-public reel) and limitations, which would benefit completeness.

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 description does not add significant meaning beyond the schema, which already describes the 'url' parameter as 'Public Instagram Reel URL'. Schema coverage is 100%, 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 (extract audio) and resource (Instagram Reel), and specifies the output (direct URL to m4a container). It distinguishes from sibling tools by focusing on audio extraction rather than video or image downloads.

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 mentions use cases ('trending-sound research and remix reference'), providing context for when to use the tool. However, it does not explicitly state when not to use it or mention alternatives like download_reels for full video with audio.

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 provided, so description carries full burden. It indicates a read-only transformation (convert) with no destructive side effects. Does not discuss auth, rate limits, or output format, but acceptable for a simple conversion tool.

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, no filler. First sentence states action and scope; second lists styles and usage option. Front-loaded and efficient.

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, usage, and parameter behavior. Lacks details on return format (likely a list of styles with transformed text), but given low complexity and no output schema, it is nearly complete.

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 description adds meaning: explains that style is optional and lists all available style names. This surpasses the schema's minimal 'Optional single style name' description.

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?

Description clearly states the tool converts plain text into Instagram-compatible Unicode fonts for bio, name, and captions. Lists all 22 supported styles, distinguishing it from sibling tools which focus on other Instagram utilities.

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 says when to use (for bio, name, captions) and how to invoke (pass one style or omit for all). However, it does not mention when not to use or compare to alternatives, though no direct alternative exists among 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?

No annotations provided, so description bears full burden. It states it returns templates from a library (non-destructive), but lacks details on authentication, rate limits, potential errors, or whether external calls are made.

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, front-loaded with purpose, no extraneous words. Efficient and easy to parse.

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 generation tool with no output schema, the description covers what it does, what it returns, and optional parameters. It could specify return format or examples, but is largely complete.

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%; all parameters are described. The description adds value by noting country and language are optional for locale-native hooks, but does not add new meaning beyond reinforcing optionality.

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 generates first-second Instagram Reels opening hooks for a niche, using a specific verb and resource. It is distinct from sibling tools like download or font generators, providing unique purpose.

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 implied by the tool name and description: use to generate hooks for a niche. No explicit when-to-use or alternatives are mentioned, but it's clear from context.

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 provided, so description is the sole source. It mentions the data source (Buffer 2026) and what is returned (5 slots + heatmap), but does not state whether it is read-only, error handling for unsupported countries, or any other behavioral traits.

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?

Three sentences with no wasted words. First sentence states purpose, second provides source credibility, third lists supported markets. Front-loaded and efficient.

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 tool with one parameter and no output schema, the description covers purpose, return content (5 slots + heatmap), data source, and supported countries. It is complete enough for an agent to use 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 coverage is 100%, and the description does not add significant meaning beyond the schema's description for the 'country' parameter. The supported market list is already in 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 data-driven optimal Instagram posting windows for a country, specifying the verb 'return' and the resource 'posting windows'. It distinguishes itself from sibling tools (e.g., download_photo, engagement_calculator) by focusing on time-to-post data.

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 the tool (for country-level posting windows) and lists supported markets, but does not explicitly state when not to use it or suggest 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?

No annotations are provided, so the description bears full responsibility for disclosing behavioral traits. It does not mention whether the tool is read-only, requires authentication, or has side effects. As a data retrieval tool, it is likely safe, but the description does not affirm this.

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?

Three sentences, no fluff. First sentence states purpose, second adds output detail, third lists markets. Information is front-loaded and every sentence is informative.

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 no output schema, the description gives output structure (Reels hook + hashtag set). It covers all parameters and provides market list. It could mention pagination behavior or max date range, but is adequate for a filtered listing 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?

Schema coverage is 100% and each parameter is described. The description adds value by enumerating specific market codes, clarifying the meaning of 'GLOBAL', and specifying the date format (ISO YYYY-MM-DD). This goes 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?

Description clearly states it 'return the Instagram content calendar entries for a market' with optional filters, specifying each entry has a Reels hook and hashtag set. This verb+resource+detail distinguishes it from sibling tools which focus on downloads, audits, or specific elements.

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 mentions markets and advises using 'GLOBAL' for cross-market dates. While it doesn't explicitly state when not to use it or name alternatives, sibling tools are clearly different in function, making usage context clear.

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 provided, so description carries full burden. It discloses the read-only nature implicitly (listing) and details output fields, but does not mention any rate limits, side effects, or further behavioral traits.

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?

Single sentence, front-loaded with verb and resource, efficiently conveys all essential information without waste.

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 simplicity of the tool (one optional parameter, no output schema), the description adequately covers the output and purpose. Could be improved by noting that the list is static and not dynamic, but overall it's sufficient.

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% for the single parameter, so the description adds no new meaning beyond the schema. Baseline score of 3 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?

Description clearly states the action (List) and resource (curated Instagram hashtag seed niches), specifies the fixed count (25) and the return fields (slug, human label, description, category grouping). It distinguishes from sibling search_hashtags by indicating this is a curated list.

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 explicit guidance on when to use this tool versus alternatives like search_hashtags. The description only states what it does, not the context or exclusions, leaving the agent to infer.

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 full burden. It discloses two key behaviors: results are not cached/fabricated and are shaped by locale. This is substantial, though it omits potential rate limits or auth requirements.

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, all essential. No filler, front-loaded with the core action, and each sentence adds distinct value.

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 two simple params and no output schema, the description covers key behaviors and purpose. It could briefly reference siblings to help selection, but is otherwise complete for a straightforward search 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?

Schema coverage is 100%, so description adds only marginal value. It confirms 'topic' is free-form and elaborates on 'locale' by stating it shapes tag mix, which complements the schema's default value mention.

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 ('Live-search'), the resource ('Instagram's public hashtag index'), and the output ('real post counts'). It distinguishes itself implicitly from siblings like 'audit_creator_hashtags' or 'get_hashtag_niche' by emphasizing live, uncached results.

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?

While no explicit alternatives or exclusions are given, the description provides context on when to use (for real-time, uncached data) and how country/language affect results. This gives clear situational guidance without contrasting siblings.

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