encode-toolkit

Server Quality Checklist

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Latest release: v0.3.0
Disambiguation5/5
Each tool has a clearly distinct purpose: searching experiments vs. files, downloading batches vs. specific files, tracking vs. comparing, etc. No two tools perform overlapping functions, and descriptions clearly differentiate them.
Naming Consistency5/5
All 20 tools follow a consistent 'encode_verb_noun' pattern in snake_case. Verbs like get, list, search, track, compare are used uniformly, making the tool surface predictable and easy to navigate.
Tool Count5/5
20 tools is well-suited for the ENCODE domain, covering discovery, retrieval, tracking, comparison, citations, provenance, and credentials. Each tool earns its place without being overwhelming.
Completeness5/5
The toolkit covers the full lifecycle: data exploration (search, facets, metadata), retrieval (download, batch download), local management (track, list, export, summarize), comparison, citations, references, provenance tracking, and credentials. There are no obvious gaps for a comprehensive ENCODE workflow.
Average 4.6/5 across 20 of 20 tools scored. Lowest: 3.8/5.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 2 commits in the last 12 weeks
- Last stable release on March 21, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under AGPL 3.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, not destructive, and idempotent. The description adds context about return structure and export capabilities but does not disclose additional behavioral traits beyond the annotations. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with sections for purpose, usage, args, and returns. Moderately concise; every sentence adds value. Could be slightly tighter but effective overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 parameters) and the presence of an output schema, the description provides sufficient context: lists return fields, export options, and a usage section. No major gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description's 'Args' section explains both parameters in detail, including the meaning of accession and the available export_format enum values. This compensates fully for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets publications and citations for tracked experiments, listing returned fields (authors, journal, DOI, PMID) and export formats. However, it does not explicitly differentiate from a potentially similar sibling tool 'encode_get_references', which may serve a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Includes a dedicated 'WHEN TO USE' section and mentions related tools. Provides guidance on export formats for reference managers. Lacks explicit exclusions or alternatives for when this tool should not be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds that the tool shows the provenance chain and returns JSON, and explains the behavior of tracing back to original data, which adds value beyond annotations. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with headers for 'WHEN TO USE' and 'RELATED TOOLS', and it includes parameter descriptions. It is appropriately sized, with every sentence adding value, though it could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema and annotations covering safety, the description sufficiently explains the purpose, parameters, and return type. It is complete enough for an agent to use the tool correctly, though more detail on the output format could be included.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage), but the description clarifies each parameter: 'file_path: Get provenance for a specific derived file' and 'source_accession: List all files derived from a specific ENCODE accession'. This adds meaningful semantics that the schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get provenance information for derived files' and explains it traces the chain back to original ENCODE data including tools and parameters. It also references a related sibling tool, distinguishing it from others.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a 'WHEN TO USE' section and mentions a related tool, but does not explicitly state when not to use it or offer alternatives beyond one sibling. The distinction between the two parameters (file_path vs source_accession) is given in the parameter descriptions, but not in a clear usage scenario.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate a write operation (readOnlyHint=false) that is non-destructive and idempotent. The description adds that it creates a 'link' and returns JSON, but does not elaborate on side effects, authentication, or duplicate handling beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a brief summary, cross-server bridge context, usage scenario, dedicated sections for WHEN and RELATED TOOLS, and clear parameter documentation. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (4 parameters, 3 required) and presence of an output schema, the description covers purpose, usage, and parameters adequately. The return description is minimal but acceptable. A slightly more detailed return format would elevate completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description provides thorough explanations for each parameter, including format examples, enum values, and usage contexts (e.g., 'experiment_accession: ENCODE experiment accession (e.g., "ENCSR133RZO")'). This fully compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the action: linking an external reference to a tracked ENCODE experiment. It provides concrete examples (PubMed, DOI, GEO) and distinguishes from sibling tools like encode_get_references which retrieve references.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
A 'WHEN TO USE' section explicitly states the tool's purpose for attaching external IDs after finding a paper. Related tools are mentioned, but no direct exclusion or alternative scenarios are provided, leaving some ambiguity about when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a safe read-only operation. Description adds value by specifying the types of identifiers returned and that they can be passed to external tools, but does not disclose additional 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with sections and bullet points. Slightly redundant between the first sentence and the WHEN TO USE section, but overall efficient and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and annotations, the description covers the core functionality well. Mentions integration with PubMed/bioRxiv, which is useful context. Lacks error or edge-case handling, but acceptable for this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description thoroughly explains both parameters: experiment_accession and reference_type with its enum values. This compensates fully for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool retrieves external references (PMIDs, DOIs, etc.) linked to experiments. Distinguishes from siblings by mentioning related tools encode_link_reference and encode_get_citations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Includes a WHEN TO USE section explaining the tool is for retrieving references to pass to other tools (e.g., PubMed). Mentions related tools but does not explicitly state when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds behavioral context such as returning JSON with results, total count, and pagination. No contradictions or missing critical information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a clear purpose statement, illustrative examples, usage notes, and parameter list. It is front-loaded and each section adds value, though slightly verbose in places.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (15 parameters, no enums, but output schema exists), the description comprehensively explains usage with examples, pagination, and relationship to siblings. It covers all key aspects for effective invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by listing all 15 parameters with brief, informative descriptions and concrete examples of usage. While not exhaustive, it adds significant meaning beyond the schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search files across ALL experiments with combined experiment + file filters.' It provides multiple examples and explicitly distinguishes itself from sibling tools like encode_list_files by emphasizing cross-experiment capability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes a 'WHEN TO USE' section that advises using this tool for cross-experiment file discovery and compares it with encode_list_files. However, it does not explicitly state when not to use it or provide specific exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, non-destructive, and idempotent. The description adds that the output includes specific fields, filters support partial matching, and that generated PMIDs are usable with PubMed MCP tools. However, it does not disclose potential export limits or pagination behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with sections for purpose, content details, usage context, related tools, parameters, and returns. Every sentence serves a purpose, and the most important information (what it exports and format options) appears first.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description adequately explains what the tool does, its parameters, and how results can be used. It covers filtering, format variants, and integration with other tools, making it sufficiently complete for an agent to understand and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 4 parameters with no descriptions (0% coverage). The description compensates by explaining format options with use cases (csv for Excel, tsv for R/pandas, json for programmatic use) and clarifying that filter parameters use partial matching. This adds meaningful context beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Export tracked experiments as a table (CSV, TSV, or JSON)' and lists included metadata, publication counts, PMIDs, and derived file counts. It distinguishes from related tools like encode_list_tracked and encode_summarize_collection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes a 'WHEN TO USE' section ('Use to create shareable tables... for manuscripts and reports') and lists related tools. It explains the output's utility with PubMed MCP tools, but does not explicitly state when not to use or provide alternative selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds that it returns a JSON list, but does not provide additional behavioral details beyond what annotations convey. There is no contradiction, but the description adds limited transparency beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with sections (purpose, when to use, related tools, args, returns). While slightly lengthy, every sentence adds value and the key information is front-loaded. Minor reduction could be possible, but overall concise for the coverage provided.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one parameter and an output schema (mentioned as JSON list), the description covers all essential aspects: purpose, usage context, all parameter options with examples, and return type. It is complete and leaves no ambiguity about how to use the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by documenting each enum value with examples (e.g., 'assays: Available assay types (Histone ChIP-seq, ATAC-seq...)). This adds significant meaning beyond the schema's enum list, making parameters self-explanatory.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get available filter values for ENCODE searches' with a specific verb and resource. It distinguishes itself from sibling tools like encode_search_experiments by focusing on retrieving valid filter values rather than executing searches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly includes 'WHEN TO USE' and 'RELATED TOOLS' sections. It advises using this tool before searching to prevent typos and mentions alternative tools (encode_get_facets, encode_search_experiments), providing clear context for when to use this tool versus others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds that the tool returns JSON with metadata and tracker stats, and notes it shows 'local library' and includes publication/derived file counts. This adds behavioral context beyond annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a one-sentence purpose, a usage section, args list, and returns statement. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 optional params, no required params, output schema exists), the description covers purpose, usage, parameter semantics, and return value. Annotations provide safety context. No gaps for effective agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% description coverage, but the description provides clear semantic meaning for each parameter: assay_title, organism, and organ filters with partial match behavior. While it lacks format constraints or examples, it compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool lists all locally tracked experiments with optional filters. It distinguishes from siblings by specifying 'tracked experiments' and referencing related tools like encode_summarize_collection. The verb 'list' and object 'tracked experiments' are clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes a 'WHEN TO USE' section advising to use for seeing all experiments in the local library and mentions filtering capabilities. It lists related tools (encode_summarize_collection, encode_export_data), providing context for alternatives. However, it does not explicitly state 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate read-only, idempotent, and non-destructive behavior. The description adds value by listing the compared fields (organism, genome assembly, etc.) and mentioning the output format, which are beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concisely structured with a clear purpose, comparison details, prerequisites, usage guidance, and parameter documentation in a well-organized format without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers prerequisites, parameter semantics, and what fields are compared. It references an output schema, which is sufficient given the existence of a structured output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description explains both parameters with examples (e.g., 'ENCSR133RZO') and context that they are accession strings of tracked experiments.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyze whether two ENCODE experiments are compatible for combined analysis.' It specifies the verb (analyze/compare) and resource (two experiments), and distinguishes from siblings by requiring prior tracking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes explicit 'WHEN TO USE' guidance and prerequisites: 'Use to check if two experiments are compatible for combined analysis. Both must be tracked first (use encode_track_experiment).' It also lists related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description confirms it is a listing operation and mentions the return format, but does not add significant behavioral context beyond what annotations provide. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a concise summary, followed by examples, parameter list, usage guidance, and related tools. It is front-loaded and every section is informative and necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (9 parameters, 1 required) and the presence of an output schema, the description adequately covers functionality, examples, common values, and return type. It is complete for an agent to correctly select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema_description_coverage is 0%, so the description bears full responsibility. It provides detailed explanations for all 9 parameters, including common values and examples (e.g., file_format: 'Common file_format values: "fastq", "bam", "bed", ...'). This adds substantial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists files for a specific ENCODE experiment with optional filters. It distinguishes from siblings like encode_search_files (which searches across experiments) and encode_get_file_info (which gets info for a single file).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states 'WHEN TO USE: Use to browse files within a known experiment. Use encode_search_files instead to find files across experiments.' It also provides a list of related tools, offering clear guidance on when to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the description doesn't need to repeat that. It adds value by noting partial match parameter behavior, but no extra details on auth or rate limits. Still, it goes beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections (description, when to use, related tools, args). The phrase 'bird's-eye view' appears twice, slightly redundant, but overall concise and informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists, the description appropriately summarizes return type (JSON summary). Covers parameters, usage context, and grouping dimensions. No gaps for a summarization tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description compensates by explaining each parameter's purpose (filter by assay, organism, organ) and noting partial match behavior. Lacks format details but provides essential context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool summarizes tracked experiments with grouped statistics, specifying grouping dimensions (assay, target, organism, etc.) and distinguishing it from siblings like encode_list_tracked and encode_export_data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit WHEN TO USE guidance is provided: 'best for 10+ tracked experiments' and 'bird's-eye view.' Also lists related tools (encode_list_tracked, encode_export_data) to help differentiate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that the tool fetches external data, stores in a local SQLite database, and associates publications and pipeline info. Annotations already indicate idempotency and open-world behavior, so the description adds useful context without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured with a clear first sentence, metaphor, usage guidelines, and parameter list. While slightly verbose, every section adds value. Could be more concise but still effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and annotations, the description covers the main functionality and use case. Minor omission: no mention of error handling for invalid accessions, but overall sufficient for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by explaining each parameter: accession (example), fetch_publications (default true), fetch_pipelines (default true), and notes (optional). This adds meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('track') and the resource ('experiment'), specifying that it stores metadata locally with publications and pipeline info. It distinguishes itself from siblings by explaining its unique role as a prerequisite for comparison and citation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit 'WHEN TO USE' guidance, stating it is required before using compare or citations. It also lists related sibling tools, helping the agent choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide safety (readOnlyHint=true, destructiveHint=false, idempotentHint=true). The description adds behavioral context beyond what annotations convey: it explains the tool returns 'complete experiment metadata including all associated files, quality metrics, controls, replicate information, and audit status.' No contradictions with annotations; this is excellent transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with minimal sentences, each earning its place. It is well-structured with clear sections: purpose, when-to-use, related tools, parameters, and returns. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
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, rich annotations, output schema exists), the description fully explains the return value (files, quality metrics, controls, replicates, audit status). It covers all necessary context for proper invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter (accession) exists, and schema coverage is 0% (no description in schema). The description provides an example ('ENCSR133RZO') and explains it is an ENCODE experiment accession, adding meaning beyond the schema's title. While schema coverage is low, the description compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves full details for a specific ENCODE experiment by accession ID, using precise verbs ('Get full details') and resource ('specific ENCODE experiment'). It distinguishes from siblings like encode_list_files (lists files) and encode_compare_experiments (comparison), so the agent can select it correctly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes a 'WHEN TO USE' section specifying when to use this tool ('when you have a specific accession and need full details including files, quality metrics, and audit status'). It also lists related tools, but does not explicitly state when not to use it or alternatives. The guidance is clear but lacks exclusion conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes creating a provenance record, consistent with annotations (readOnlyHint=false, destructiveHint=false). Idempotency hinted by idempotentHint=true but not elaborated; otherwise transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with sections and bulleted args. Slightly verbose but every sentence contributes to understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all necessary aspects: purpose, usage, parameters, return value (output schema exists), and context relative to siblings. No gaps evident.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description provides thorough explanations for all 6 parameters with examples, adding substantial value over the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Log a file you've derived from ENCODE data for provenance tracking' with specific examples. It distinguishes from siblings like encode_get_provenance and encode_download_files.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly includes 'WHEN TO USE' and 'RELATED TOOLS' sections, guiding the agent on appropriate context and alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds useful behavioral context, such as pagination via limit/offset, default status 'released', and that it returns JSON with results, total count, and pagination info. No contradictions, and the description enhances transparency beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear opening, examples, common values, usage guidance, and parameter list. It is front-loaded with purpose. However, it is somewhat lengthy due to the many examples and parameter details, but this is justified by the need to compensate for zero schema coverage. Nearly all sentences earn their place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (21 parameters, no required fields, no enums, has output schema), the description is remarkably complete. It explains the return format (JSON with results, count, pagination), provides usage examples, lists common values, and gives guidance on when to use alternative tools. The output schema existence reduces the need to detail return values, but the description handles it well.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides detailed explanations for all 21 parameters, including common values, defaults, and usage examples. Examples like 'assay_title="Histone ChIP-seq", organ="pancreas", biosample_type="tissue"' illustrate how to combine parameters effectively. This fully compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search ENCODE experiments with comprehensive filters.' The verb 'search' and resource 'ENCODE experiments' are specific. Examples and common values further clarify the scope, and the tool is distinguished from siblings like encode_search_files and encode_get_facets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes explicit 'WHEN TO USE' guidance: 'Use as the primary entry point when users want to find experiments. Start with encode_get_facets if unsure what filters to use.' It also lists related tools, providing clear context for when to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds detail about returning faceted counts and that it is exploratory, not modifying data. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a header, usage guidelines, examples, and return type. Every sentence adds value, and it is front-loaded with the purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description explains the return format ('JSON with facet names and term counts'). All parameters are covered with examples, making it complete for exploration.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description lists all 5 parameters with clear explanations and examples (e.g., organ='pancreas'). This adds significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get live filter counts from ENCODE to discover what data is available.' It specifies the verb (get), resource (filter counts), and distinguishes from sibling tools like encode_search_experiments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit 'WHEN TO USE' section: 'Use to explore what data exists before searching. Shows counts per filter value. Best first step for unknown datasets.' Also lists related tools and provides examples.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructive and idempotent behavior. The description adds security context (OS keyring storage, no plaintext) and confirms action results as JSON. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections: purpose, security note, when-to-use, related tools, args, returns. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a credential management tool with output schema present, the description covers all necessary information: purpose, usage, parameter details, security, and return format. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema coverage, the description thoroughly explains each parameter: action's three values and when access_key/secret_key are required, adding meaning beyond the schema's enum and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool manages ENCODE API credentials for restricted/unreleased data, with specific actions (store, check, clear). It is distinct from siblings like encode_search_experiments which focus on data queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use (only for unreleased/restricted data) and when not (public data needs no auth). Names related tool encode_search_experiments, providing clear context for alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the two-step process (search then download) and the default dry_run mode. The annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=true, openWorldHint=true) are consistent with the description's behavior: downloading is not read-only but is idempotent and not destructive. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is comprehensive but slightly verbose. It includes a parameter list with repeated explanations; some could be shortened. However, it is well-structured with clear sections (purpose, behavior, when-to-use, examples, args) and front-loads key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (15 parameters, 1 required) and the presence of an output schema, the description covers all necessary aspects: purpose, behavior, when-to-use, examples, and parameter descriptions. The return value is described as 'JSON with download preview or download results.' No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates by explaining each parameter's meaning, default values, and example values (e.g., file_format='bed', assay_title='Histone ChIP-seq'). This adds significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search for files and download them all in batch.' It uses specific verbs ('search and download') and resource ('files'). It distinguishes itself from siblings encode_download_files (for specific files) and encode_search_files (only search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'Use for searching and downloading files in one step.' Provides guidance to always use dry_run=True first. Names alternative tool for specific file accessions: 'use encode_download_files.' Lists related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses MD5 verification, concurrent downloads, and skip-if-already-downloaded behavior. Annotations indicate readOnlyHint false, destructiveHint false, idempotentHint true, openWorldHint true, with no contradictions. The description adds valuable context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a brief summary, detailed features, usage guidance, and a parameter list. It is concise, with no extraneous information, and each sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 4 parameters, 0% schema coverage, output schema presence, and annotations, the description provides complete guidance: parameter details, return format, and behavioral traits. Nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description includes a detailed 'Args' section explaining each parameter with examples, defaults, and enum options for 'organize_by'. This fully compensates for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The name and title clearly indicate downloading ENCODE files. The description specifies 'Download specific ENCODE files by accession to a local directory,' using a specific verb and resource, and distinguishes from sibling tools like encode_batch_download.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states 'WHEN TO USE: Use for downloading specific files by accession. For bulk downloads, prefer encode_batch_download.' It also lists related tools, providing clear guidance on when to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds that it returns JSON with specific metadata fields, consistent with annotation. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Short, front-loaded with purpose, then structured sections for usage, parameters, and returns. Every sentence adds value; no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one parameter and an output schema, the description covers all necessary context: purpose, when to use, parameter meaning, and return type. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Single parameter 'accession' is explained in the description as 'File accession ID' with an example value, compensating fully for 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description explicitly states 'Get detailed information about a specific ENCODE file' with a clear verb and resource. It lists specific metadata fields (size, md5, assembly), distinguishing it from siblings like encode_download_files (download) and encode_list_files (list).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a dedicated 'WHEN TO USE' section: 'Use when you need detailed metadata for a specific file' and lists related tools, giving clear usage context and 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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