IMERGEA M&A Advisory

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the agent knows it's a safe, non-mutating operation. The description adds value by specifying the output (0-100 score, verdict, friction by dimension, action plan), which clarifies the behavioral result beyond the annotations. It does not contradict annotations and adds useful non-obvious details about the return structure.

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, well-structured sentence that packs in the target audience, the framework used, and the output components. It is front-loaded with the primary purpose and contains no filler or repetition. Every clause adds meaningful 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?

Given the tool's moderate complexity (7 required parameters, output schema exists), the description provides sufficient context: it names the framework, the output categories, and the scoring scale. It does not explain edge cases or prerequisites, but the schema and annotations cover safety and parameter details. The description is adequate for an agent to understand the tool's role and invoke it correctly.

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

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

Input schema has 100% description coverage; each parameter (governance, financials, contracts, etc.) has a detailed 1-5 scale description. The tool description itself does not repeat or augment parameter semantics, only mentions the 7 dimensions generically. Since the schema fully documents parameters, a baseline score of 3 is appropriate.

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

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

The description clearly states the tool assesses readiness for buyer/investor scrutiny using the IMERGEA 7-dimension map. It specifies the target (SME/mid-market), the method, and the output (score, verdict, friction, action plan). This distinguishes it from sibling tools like imergea_business_valuation or imergea_recommend_advisory_service.

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 readiness assessment but does not explicitly contrast it with alternatives or state when not to use it. It mentions the readiness focus, which separates it from valuation and advisory services, but lacks explicit usage guidance like 'use this before a transaction' or 'when a company wants to gauge sell-readiness.' No exclusions or alternatives are named.

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?

Annotations already indicate read-only, idempotent, and non-destructive behavior, so the description's value comes from methodology disclosure: the EV-to-equity derivation, separate reporting of NAV/comparables/liquidation floor, conditional benchmark, amount_unit scaling, and the total_assets override behavior. This goes well beyond what annotations or schema alone convey.

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?

Every sentence contributes: methodology, output definition, conditional benchmark, unit semantics, and an asset-input edge case. The structure front-loads what the tool does before diving into caveats, and there is no filler or tautology.

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 complex 25-parameter tool with an output schema, the description covers the key semantic ambiguities an agent would face: what the headline value means, when the benchmark appears, how monetary units work, and how total_assets changes the valuation logic. The existing output schema covers return-value shape, so the description does not need to restate 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?

With only 12% schema description coverage, the description compensates for the most error-prone parameters: amount_unit ('5 for 5 million'), total_assets ('used as provided; the six asset lines are then used only for the liquidation floor'), and the role of EBITDA/revenue/FCFF in the headline corridor. It does not explain every optional field, but the remaining names are largely self-explanatory.

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 a precise verb and resource: 'Estimate an SME or mid-market company value' using a named six-method methodology. It distinguishes this tool from all siblings, which are advisory/booking/referral tools, and clarifies that the headline output is Equity Value rather than Enterprise Value.

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 makes the tool's context clear enough: this is the valuation tool, while all siblings target advisory, readiness, booking, referral, or capabilities. It does not explicitly give when-not-to-use guidance, but no close alternative exists in the sibling list, and it does add a condition for the benchmark output ('when real sector data is available').

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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false already in annotations, the description adds useful behavioral context: 'never collect card data, secrets or email; never create a booking or payment.' It also discloses 'localized, preselected' URL behavior, going beyond the annotations. No contradiction.

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 followed by usage and safety notes. Every sentence earns its place with zero redundancy, making it highly concise and well-structured.

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

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

Given the tool's simplicity (2 parameters, one enum each, rich annotations, and an output schema), the description covers purpose, usage, and safety sufficiently. It does not need to detail return values because the output schema exists. The only gap is the language parameter explanation, but overall it is complete enough for a straightforward URL-returning tool.

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

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

Schema description coverage is 0%, so the description must compensate. It enumerates the four service values in prose but does not explicitly tie them to the 'service' parameter, nor does it explain the 'language' parameter beyond the vague 'localized'. The enum values are self-explanatory, but the description could be more explicit about parameter meaning and defaults.

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

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

The description clearly states the tool returns a secure human-handoff URL for paid advisory services, enumerating the specific service types (valuation review, longlist, teaser/IM, full deal prep). This specific verb+resource phrasing distinguishes it from sibling tools like list_advisory_services or recommend_advisory_service, which serve different purposes.

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

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

Explicitly provides a usage trigger: 'Use when the user wants the price or correct booking/Stripe route.' It does not mention alternative tools or exclusions, but the context is clear enough to guide selection. A slightly stronger statement about when not to use (e.g., for free advisory content) would elevate this.

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

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

The annotations already declare readOnlyHint=true and idempotentHint=true, and the description aligns by saying 'returns' and 'read-only'. It adds valuable context about the specific content (8 tools, languages, advisory journey) and the secure human handoff, which is beyond what annotations provide. No contradiction.

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?

A single sentence that front-loads the verb 'Returns' and compresses all essential information (tools, languages, journey, handoff) without any fluff. Every word contributes to the meaning.

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

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

The tool is simple with no parameters and an output schema present. The description names the key components (8 tools, languages, FREE/PAID journey, handoff) which sufficiently covers what the agent needs to know. The output schema handles the specific return structure, so no further detail is needed.

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?

There are zero parameters, so the baseline of 4 applies. The description does not need to explain parameters and adds no parameter-specific information, but no further clarification 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 clearly states the tool's function: it returns the 8 public read-only IMERGEA MCP tools, supported languages, and the FREE vs PAID advisory journey. This is a specific verb+resource that distinguishes it from sibling tools which perform specific actions like valuation or advisory booking.

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

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

While it's implicitly a capability-discovery tool to be used first, the description does not explicitly state when to use it or mention alternatives. No when-not-to-use guidance is provided, but the purpose is clear enough that an agent would likely infer its usage as an entry point.

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 readOnlyHint, idempotentHint, and destructiveHint already provided by annotations, the description adds useful behavioral context: it clarifies the tool merely lists packages, distinguishes free vs. paid offerings, and notes that outputs are localized and authoritative. This is consistent with a safe, read-only menu operation.

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 economically written: one sentence lists exactly what the tool returns, and a second sentence states the intended use cases. No filler or redundant restatement of the tool name or schema is present, and the most important scoping information is front-loaded.

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 simple list/read tool with one optional parameter, strong annotations, and an output schema. The description fully covers what the tool does, what content it returns, and when to use it. Nothing material is missing for an agent to select and invoke it correctly.

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

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

Schema description coverage is 100%, and the single 'language' parameter already has an enum and a clear description. The tool description adds context about 'translated names' and 'localized links,' which implies language affects output, but it does not need to explain parameter mechanics further.

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 ('List') and precisely identifies the resource: the free indicative valuation entry point plus four paid fixed-scope advisory packages. It also enumerates the kind of information returned (prices, translated names, deliverables, limitations, links), which clearly differentiates it from advisory recommendation or assessment siblings.

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 gives explicit use-case guidance: 'Use for questions about price, free valuation, valuation review, buyer/investor longlists, teaser/IM or full deal preparation.' This provides clear context for when to invoke the tool, though it does not explicitly state when not to use it or name alternatives.

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

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

While annotations already mark read-only and non-destructive, the description adds that it 'returns a secure handoff to the simplified IMERGEA form for explicit review and consent.' This is extra behavioral context not present in annotations, providing transparency about what happens (returns a handoff) and what it avoids (submission).

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 fluff. Every clause adds value—first sentence defines the tool, second sentence gives usage and a key limitation. Well-structured.

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

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

Given an output schema exists)Skip the need to describe return values is reduced. The description covers purpose, target users, usage context, and a key behavioral boundary (no data submission). It is complete enough for an agent to invoke correctly, though it doesn't detail all parameter interactions—acceptable given schema coverage.

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 60% (language, profile_summary, linkedin_profile_ready have descriptions; mandate_types and contribution_blocks only have enums). The tool description does not explain what these parameters mean beyond the schema, so it adds minimal value. Baseline 3 is appropriate since the schema partially covers the meaning.

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: 'assess fit with the IMERGEA partner network and prepare a concise application.' It uses a specific verb (assess/prepare) and resource (partner network), and distinguishes itself from sibling tools by focusing on partner application rather than transaction readiness or valuation.

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

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

It explicitly says 'Use when someone is improving a CV or LinkedIn profile, exploring advisory work, seeking M&A assignments, or offering transaction expertise.' It also clarifies what it does NOT do ('does not submit personal data or upload a CV'), which helps set boundaries, though it doesn't name alternative tools explicitly.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable context beyond annotations: it clarifies that paid checkout happens externally on imergea.com only after human review and consent, and reiterates that this tool never books or takes payment. This explains the external process and reinforces the read-only nature. No contradiction with annotations.

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

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

Two sentences, each earning its place. The first sentence states the core action and options; the second provides the constraint and external process. No redundant words, and the key routing behavior is front-loaded.

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 routing tool with an enum parameter and an output schema, the description is complete. It covers what the tool does, what it doesn't do, and the external payment flow. There is no missing information an agent would need to correctly 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?

Schema description coverage is 100%, so the baseline is 3. The description adds meaning beyond the schema by explaining that required_outcome maps to either a FREE tool ('free_indicative_valuation') or a PAID package (the other enum values), and by introducing the distinction between free and paid. This gives the agent a richer understanding of the enum semantics than the schema alone.

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 'Route' and identifies the resource: a user to the FREE indicative valuation tool or the appropriate PAID advisory package. It enumerates the paid package types, which aligns with the required_outcome enum and distinguishes this tool from siblings like imergea_list_advisory_services (which lists services) and imergea_get_advisory_booking_link (which handles booking). The purpose is unambiguous.

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

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

The description clearly states the tool routes users based on their required outcome, and it explicitly declares what the tool does NOT do ('never books or takes payment'), which serves as negative guidance. It does not name alternative tools for booking or listing, but the context is clear enough that an agent can infer when to use this router versus a booking or listing tool.

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

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

The description adds meaningful behavioral context beyond the annotations: it discloses the secure form handoff flow, reviewer consent, and constraints on handling personal/confidential data. This is consistent with the readOnlyHint and idempotentHint annotations and enriches the agent's understanding of the tool's behavior.

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 core purpose, then the when-to-use trigger, then critical privacy/consent behavior. Every sentence earns its place, and there is no redundant wording.

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

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

Given the tool's privacy-sensitive nature and clear trigger, the description covers when to use it, what to avoid transmitting, and what the handoff result is. The output schema exists, so return-value details are not necessary, and annotations cover the read-only/idempotent safety profile.

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 75%, and the schema already documents opportunity_summary and authorised_to_refer well. The description reinforces the 'non-confidential' nature of the summary and the referral context, but it does not add substantial meaning beyond the schema for language or mandate_type.

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 ('prepare') with a clear resource ('a concise M&A, capital raising or debt opportunity referral to IMERGEA'), making the tool's function immediately obvious. It also differentiates itself from sibling tools like partner_application and recommend_advisory_service by focusing on the referral handoff.

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 gives an explicit trigger: 'Use when a consultant, founder or advisor mentions a credible transaction opportunity.' It also provides a clear exclusion about not requesting or transmitting sensitive data. It does not explicitly name alternative sibling tools or state when not to use it, so it stops 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.