UluAlgorandMCP

by NautilusOSS

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Latest release: v1.0.0
Disambiguation4/5
Tools are mostly distinct: protocol operations are split into list, get, contracts, and summary, and name tools are clearly separated. However, identify_application and get_contract_role overlap since identify_application already returns the role, which could cause misselection.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case, using verbs like get, identify, resolve, and search. The convention is uniform and predictable across the entire set.
Tool Count5/5
10 tools is well within the ideal 3-15 range and fits the server's purpose of providing Algorand protocol, contract, asset, and name lookups. Each tool covers a distinct aspect without unnecessary bloat.
Completeness4/5
The surface covers protocol discovery, application/asset identification, contract roles, and name resolution (forward, reverse, search), which is comprehensive for a read-only static registry. Minor gaps exist, such as no direct list-all-assets or list-all-applications, but these are not critical dead ends.
Average 3.8/5 across 10 of 10 tools scored. Lowest: 3.2/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
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.
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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.
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source of behavioral info. It implies a read-only list operation but does not disclose what 'all known contracts' includes, whether results are paginated, or what fields are returned. This is insufficient for an agent to anticipate side effects or output characteristics.
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 a single, focused sentence with no redundant info. It is appropriately concise and front-loaded with the key action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of annotations and output schema, the one-sentence description is too sparse. It does not explain the return format, any constraints on protocolId, or link to protocol discovery, leaving significant gaps for an agent to use the tool correctly in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% since protocolId has a description in the schema. However, the tool description adds no additional meaning about the parameter's format or relationship to other tools. Baseline 3 applies because the schema already documents the parameter adequately.
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 uses a specific verb 'List' and clearly states the resource 'all known application contracts for an Algorand protocol', which distinguishes it from sibling tools that retrieve protocol metadata or summaries. The intent is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like get_protocol or get_protocol_summary, nor any mention of prerequisites (e.g., needing a valid protocolId from get_protocols). The description only states what it does, not when it is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. 'Get' suggests a read-only operation, but the description does not confirm this, nor does it mention any constraints, limitations, or return format. It adds little beyond the tool's name.
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 a single sentence that is clear, front-loaded, and free of superfluous words. It efficiently states the action and object.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool, the description is minimally adequate, but it omits what 'detailed information' encompasses. Given the existence of sibling tools like get_protocol_summary and get_protocol_contracts, a clearer boundary would improve completeness. No output schema exists, so a bit more detail on the return value would be warranted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully describes the only parameter (protocolId) with type and examples, and schema coverage is 100%. The tool description adds the phrase 'by ID', which aligns with the schema but no extra semantic value beyond what the schema already provides. Baseline 3 applies.
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 'Get detailed information about a specific Algorand protocol by ID', using a specific verb and resource. It distinguishes from siblings like get_protocols (plural) and get_protocol_summary by emphasizing 'specific' and 'by ID', though it doesn't elaborate what 'detailed information' includes.
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 intended use is implied: call this when you have a specific protocol ID and want detailed info. However, there is no explicit when/when-not guidance or mention of alternatives such as get_protocol_summary or get_protocol_contracts, which could be more appropriate for narrower needs.
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?
The verb 'Get' implies a read-only operation, which is a basic behavioral trait. However, with no annotations provided, the description carries the full burden and fails to disclose other aspects like return format, error behavior, or whether the role may be unavailable. The minimal context earns a baseline score.
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 a single, direct sentence with illustrative examples and no filler. It is front-loaded with the verb and resource.
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?
For a one-parameter, read-only lookup, the description provides enough to understand what the tool does and when to call it. However, it omits details about the return type and the meaning of 'known', leaving a small gap in contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes appId as 'Application ID on Algorand' with 100% coverage. The description contributes examples of role values, which clarify the tool's output but not the parameter itself, so it adds only marginal value 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 retrieves the known protocol role for an Algorand application, with concrete examples (amm-router, name-registry, lending-pool). This is a specific verb+resource pairing that distinguishes it from sibling tools like get_protocols or identify_application.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Sibling tools such as identify_application or get_protocol_contracts may overlap in purpose, but the description doesn't address selection criteria or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavioral traits. While the verb 'Get' implies a read-only operation, the description does not explicitly state that it is safe, non-mutating, or free of side effects. It also does not mention any authentication requirements, rate limits, or error behavior, leaving these aspects opaque.
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 a single, front-loaded sentence that directly states the tool's purpose and contents. Every word contributes meaningful information, with no repetition or filler, making it optimally concise 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?
The tool has only one required parameter and no output schema, so the description partially compensates by naming the types of information returned (purpose, contracts, assets). However, it lacks details about the return format, potential errors, or any prerequisites, which would make it more complete for an agent. Given the tool's simplicity, the omission is not severe, but there is room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage for the single parameter protocolId with a helpful example ('tinyman, folks-finance'), so the schema already carries the parameter meaning. The description adds general context that the summary includes purpose, contracts, and assets, but it does not elaborate on the parameter itself beyond what the schema states.
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 uses a specific verb ('Get') with a clear resource ('concise agent-friendly summary of an Algorand protocol') and specifies the scope ('including its purpose, contracts, and assets'). It effectively distinguishes itself from sibling tools like get_protocol or get_protocol_contracts by emphasizing 'concise agent-friendly' and the summary nature.
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 implies the tool is for obtaining a concise, agent-friendly overview, which suggests a use case distinct from more detailed or specific sibling tools. However, it does not explicitly state when to use this tool versus alternatives like get_protocol or get_protocol_contracts, nor does it provide any exclusions or conditions.
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?
No annotations are provided, so the description must disclose behavior; it states a read-only listing operation and output fields. It doesn't mention filtering semantics or pagination, but for a simple list tool with one optional filter this is acceptable.
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?
Single sentence, front-loaded with action and resource, zero filler. It is concise yet informative.
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?
With one optional parameter and no output schema, the description succinctly conveys purpose and output. It could mention optional filter behavior or return shape, but these are not critical for a simple list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the type parameter with examples. The description does not add parameter-level meaning beyond noting the output includes type and description.
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 uses specific verb 'List', identifies resource 'all known Algorand protocols', and specifies output content 'type and description'. It clearly distinguishes from sibling get_protocol which targets a single protocol.
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?
Description implies usage for enumerating all protocols but provides no explicit when-to-use or alternatives. Sibling names suggest singular/detail variants, but the description itself lacks guidance.
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?
With no annotations, the description carries the transparency burden. It discloses return fields and the conditional nature of tags ('if known'), but does not mention error handling, side effects, or any access requirements. For a straightforward read-only lookup, this is moderate but not exhaustive.
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 a single, compact sentence that front-loads the action and includes essential return information. Every word earns its place.
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?
For a simple one-parameter lookup, the description is largely complete: it states the purpose and expected return content without needing an output schema. It does not specify behavior for unknown asset IDs, but given the low complexity, this is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter (assetId) is fully documented in the schema with clear meaning (0 for ALGO). The description adds no extra semantic detail beyond saying 'by ID', so it doesn't go beyond what the schema provides.
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 identifies an Algorand asset by ID and lists the returned fields (name, symbol, type, protocol association, tags). This distinguishes it from sibling tools like identify_application and protocol getters, which target different resource types.
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?
It provides clear context for when to use the tool: when you have an asset ID and need its metadata. However, it does not explicitly mention alternatives or when not to use it, so it falls short of a full 5.
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?
No annotations are provided, so the description carries the burden. It discloses that it is a read-only search returning matching .algo names, but omits details like case sensitivity, pagination, or result ordering. This is minimal but acceptable for a simple search tool.
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 two concise sentences, front-loaded with the action and resource. Every word earns its place, with no redundancy or padding.
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?
For a simple one-parameter search tool with no output schema, the description covers purpose, input type (pattern), and return value (matching names). It could mention result format or limits, but the static registry context and low complexity make this reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter documented as 'substring match against registered names.' The description restates the concept of matching but adds no new semantic detail, so the baseline score of 3 is appropriate.
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 searches the Algorand name registry by pattern and returns matching .algo names. The verb 'search' and resource 'name registry' are specific, and it distinguishes itself from sibling tools like resolve_name (exact lookup) and reverse_resolve_address.
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 provides clear context: use when you want pattern-based search against the static registry. It implies a distinction from exact-resolution siblings without explicitly naming alternatives, but the context is sufficient for an agent to select it appropriately.
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?
With no annotations, the description discloses the tool uses a static registry and returns well-known names, implying read-only and potentially outdated data. However, it does not describe return format, error behavior, or what happens if no name is found, leaving some transparency gaps.
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?
Two sentences, zero fluff. First sentence states the action and resource, second gives explicit alternative. Extremely concise and well-structured.
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?
Despite lacking annotations and output schema, the description gives enough context to select and invoke the tool: it specifies the source (static registry), the input (address), and the purpose (names lookup). The only gap is exact return shape, but for such a simple tool it's sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides complete coverage for the address parameter with clear description. The tool description adds no additional parameter semantics, but none are needed for a single, self-explanatory parameter. Baseline 3 is appropriate.
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 uses the specific verb 'look up' with a clear resource ('well-known Algorand names from the static registry') and explicitly contrasts with live resolution, distinguishing it from sibling resolve_name. It clearly states the tool's scope.
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 this tool (for static/well-known name lookup) and provides alternatives for live resolution (UluCoreMCP or NFDomains API), giving clear when-to-use and 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses what the tool returns, including the conditional 'if known', implying a lookup operation with no side effects. While it doesn't explicitly state non-destructiveness or error behavior, 'identify' strongly suggests a read-only action, and the return-field disclosure adds 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 a single, well-structured sentence. It front-loads the verb and resource, then lists the output information efficiently, with no wasted words.
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 tool with one parameter, no output schema, and no annotations, the description is complete. It explains what the tool returns and the 'if known' caveat, covering the essential information an agent needs to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the parameter 'appId' is already described as 'Application ID on Algorand'. The description adds no additional parameter semantics beyond the schema, so the baseline score of 3 applies.
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 ('Identify'), the resource ('Algorand application'), and the lookup criterion ('by ID'). It also lists the returned information (protocol, role, type, description), which helps distinguish it from siblings like identify_asset or get_protocol.
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 provides clear context: use this when you have an Algorand application ID and want its metadata. It does not explicitly name alternatives or exclusions, but the resource-specific wording differentiates it from other tools like identify_asset or get_contract_role.
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?
With no annotations, the description carries the transparency burden. It discloses the key behavioral trait: the data comes from a static registry (so it may be stale). It also states the return value (address and metadata). However, it does not enumerate what metadata is returned or mention possible errors, but these gaps are minor for a simple resolver.
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: two sentences, with the main purpose in the first sentence and the alternative in the second. Every word adds value, and it is front-loaded with the action. No filler or 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 simplicity (one parameter, no output schema), the description is largely complete: it states inputs, outputs, and usage boundary. It slightly lacks detail on the exact shape of the metadata returned, but this is acceptable for a straightforward resolver and the description is otherwise self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: the only parameter 'name' is already described in the schema with an example. The tool description repeats the example ('example.algo') and the basic purpose, but adds little new semantic meaning beyond what the schema provides. Baseline 3 is appropriate.
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 ('Resolve an Algorand name'), the resource (e.g., 'example.algo'), and the output ('to its address and metadata'). It also distinguishes itself by specifying 'from the static registry', differentiating it from sibling tools like reverse_resolve_address or search_names.
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 provides usage guidance: 'For live resolution, use UluCoreMCP or NFDomains API.' This tells the agent when NOT to use this tool and names concrete alternatives. It also implies the appropriate context (static registry) versus live lookups.
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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