nctr-mcp-server

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explicitly says 'Shows NCTR lock thresholds, multipliers, and perks' and mentions 'current balance to check tier status and progress to next tier,' making the read-only informational nature clear. It also implies behavior when no target_tier is given ('see the full progression path'), which adds useful behavioral context beyond the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences and front-loaded with the main purpose. The first sentence covers the core function, and the second specifies the exact details shown. Every phrase earns its place with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a low-complexity tool with two optional parameters and no output schema. The description fully explains both usage modes (specific tier or full path) and the kind of information returned (thresholds, multipliers, perks). It is complete enough for an agent to invoke correctly without additional detail.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters well. The description adds a slight bit of meaning ('target_tier' optionality via 'or see the full progression path' and 'current_balance' for tier status), but it does not significantly enrich the parameters beyond what the schema descriptions provide. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Check' and clearly identifies the resource: 'Crescendo status tier.' It distinguishes itself from sibling tools by naming the specific information it provides (NCTR lock thresholds, multipliers, perks) and offering two clear modes: checking a specific tier or viewing the full progression path.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly states two usage contexts: checking requirements for a specific tier or seeing the full progression path. It does not explicitly mention when not to use the tool or list alternatives, but sibling tools are sufficiently different that no exclusion is necessary. The optional parameters are not explicitly tied to usage scenarios in the description, but the context is reasonably implied.

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

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

No annotations are provided, so the description carries the full burden. It implies a read-only operation via 'Get' and indicates a time-filtered behavior ('currently active'), but it does not disclose return format, pagination, or any potential side effects. This is a minimal viable disclosure for a simple zero-param getter.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, front-loaded with the key action, and contains no wasted words. It is optimally concise for the tool's simplicity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-param read-only list tool with no output schema, the description is sufficiently complete. It states what is retrieved and the program context (NCTR). It would benefit from mentioning return structure, but this is not critical for a straightforward getter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With zero parameters, the baseline is 4. The description does not need to explain parameters, and the schema confirms no properties. No additional parameter context is required.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Get') and clearly identifies the resource ('currently active promotions, limited-time offers, and special earning opportunities'). It distinguishes itself from siblings like get_earning_rates and search_bounties, which focus on ongoing rates and specific bounties.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool: when you need currently active promotions or special offers. However, it does not explicitly state when not to use it or mention alternative tools, so it falls short of a 5.

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

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

No annotations are provided, so the description carries the burden of disclosing behavior. It states the tool 'Shows the multiplier' and notes that 'Higher tiers earn more NCTR per bounty,' which implies a read-only operation. However, it does not elaborate on return format, edge cases, or any potential limitations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three concise sentences, front-loaded with the main purpose and immediately giving the key behavior. There is no filler or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with two optional parameters and no output schema, the description provides sufficient context to understand purpose and usage. It could mention what the output looks like, but the absence is not a major gap given the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with both parameters described in the schema. The description adds context about tier comparison and tier-adjusted calculation, but it does not add significant detail beyond the schema's own descriptions. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Get') and clearly identifies the resource ('NCTR earning rates for a specific Crescendo status tier, or compare all tiers'). It also differentiates from siblings by focusing on tier-based earning multipliers, which is distinct from tier requirements or bounty search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool (checking rates for a tier or comparing all tiers) and explains the core behavior. It does not explicitly state alternatives or exclusions, but the context is clear enough for selection among the listed sibling tools.

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

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

With no annotations, the description carries the full burden. It does disclose the informational nature and the topics covered (Torus mechanism, DeFi yields, brand purchases, etc.), but it does not state return format or explicitly confirm read-only behavior. Still, 'Learn' implies no side effects, so this is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences, front-loaded with the main purpose. Every word adds value, covering the topic and the key revenue sources without unnecessary fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple no-parameter, no-output-schema informational tool, the description is fully complete. It explains what the tool teaches and the scope of content, leaving no ambiguity for the agent to select and invoke it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema is empty. According to calibration, a baseline of 4 is appropriate when there are no parameters, and the description does not need to add parameter information since there are none.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: to explain how the NCTR rewards pool is funded. It is specific about the resource (funding sources) and differentiates from sibling tools like get_earning_rates or search_bounties by focusing on the ecosystem funding mechanism.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool: when someone wants to learn about the funding sources behind Crescendo member rewards. It does not explicitly mention alternatives or exclusions, but the context is obvious enough, which matches a 4.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes what Impact Engines are, but not what the tool actually returns, whether it supports filtering, or whether it has side effects like joining a community.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences and front-loads the purpose. The additional context about Impact Engine communities is useful, though slightly verbose for a simple list tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description is minimally sufficient: the name and first sentence imply a list operation, and the schema covers the optional filter. However, return format and filtering behavior are left implicit.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description for the category parameter is 100% complete, listing all possible values. The tool description adds no parameter-specific meaning 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Discover NCTR Impact Engine communities', using a specific verb and resource. It clearly distinguishes the tool from siblings focused on promotions, requirements, funding, and search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The first sentence 'Discover NCTR Impact Engine communities' gives clear context for when to use the tool. It does not mention explicit exclusions or alternatives, but the purpose is unambiguous among the sibling tools.

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

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

With no annotations provided, the description carries the burden of disclosing behavior. It states that the tool generates a link and returns a sign-up URL plus earnings summary, but it does not mention any side effects, permissions, or whether the operation is persistent. It adds some return-value context but lacks deeper behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core purpose, and contains no redundant information. Every word contributes to understanding the tool's function and return value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one optional parameter and no output schema, the description covers the key elements: what it generates, the optional parameter, and what it returns. It is slightly incomplete in not addressing potential caveats like link expiration or authentication, but it is adequate for the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the single parameter referral_code, and the schema description already explains its purpose. The description restates that the code is optional and credits the referring member without adding meaningful new information beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a link for a new member to join NCTR Alliance, with an optional referral code. This is a specific verb+resource combination that distinguishes it from sibling tools focused on requirements, promotions, rates, funding, and bounties.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for creating onboarding links, but it does not explicitly state when to use it over alternatives or provide exclusions. No mention of when not to use it or comparisons to other tools.

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

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

With no annotations provided, the description carries the full transparency burden. It discloses return contents (name, amount, lock period, requirements) and adds the 360LOCK behavioral detail ('tokens stay yours after the lock period'). However, it doesn't mention potential quirks like result limits or ordering, but for a read-only search tool this is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with the primary purpose, then filter criteria, then return behavior and a noteworthy lock detail. Every sentence adds value with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 optional parameters and no output schema, the description covers the tool's purpose, filter dimensions, return fields, and a distinctive feature (360LOCK). It doesn't explain filter combinability or result ordering, but for a search tool this is reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with each parameter individually described. The description adds grouping and context (e.g., listing category enum values) but doesn't provide new semantic information beyond what the schema already conveys, consistent with the baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Search and filter available NCTR bounties' with specific filter dimensions (category, amount, keyword). It doesn't explicitly contrast with sibling tools like get_active_promotions, so it falls short of a 5, but the resource and verb are specific enough to distinguish it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage (search bounties when you need filtering) and lists filter options, but provides no explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives. This is implied usage rather than clear exclusions.

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