Philadelphia water and fire damage restoration: assessment, insurance, costs, and knowledge search.
Returns structured damage assessment for water and fire damage in Philadelphia residential properties. Classifies 13 damage types by severity, provides prioritized immediate safety actions, estimates restoration costs with Philadelphia market rates, and includes neighborhood-specific risk context. Based on IICRC S500/S520/S700 standards and field experience from Philadelphia restoration companies.
| Name | Required | Description | Default |
|---|---|---|---|
| damage_type | Yes | Type of water or fire damage to assess | |
| neighborhood | No | Philadelphia neighborhood (e.g., 'fishtown', 'center-city') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds useful context about standards and content, but it fails to address the annotation destructiveHint=true. While it says 'returns' an assessment, it does not clarify whether the tool has side effects or what might be destructive, leaving an important transparency gap for a mutation-flagged tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the main purpose, followed by key details. It is slightly dense but every sentence contributes; the standards citation adds credibility without excessive length.
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, the description compensates by summarizing the outputs: severity classification, prioritized safety actions, cost estimates, and neighborhood risk. It is sufficiently complete for a two-parameter tool, though it omits any mention of side effects or when to avoid using 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 coverage is 100%, so the baseline is 3. The description adds meaning by stating the tool classifies 13 damage types, which corresponds to the damage_type enum, and mentions neighborhood-specific risk context for the neighborhood parameter, going beyond the schema descriptions.
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 structured damage assessment' for water and fire damage in Philadelphia residential properties, naming a specific verb, resource, and scope. It distinguishes itself from siblings like estimate_cost and get_emergency_steps by positioning itself as a comprehensive assessment that includes those aspects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. It does not mention alternatives or exclusions, despite sibling tools like estimate_cost and get_emergency_steps that overlap with the described functionality. Usage context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns Pennsylvania insurance coverage analysis for water and fire damage claims. Evaluates coverage likelihood by HO policy type (HO-1 through HO-6), applies PA-specific regulations including bad faith statute (42 Pa.C.S. § 8371) and Act 119, and provides step-by-step claims process guidance with common denial reasons and appeals strategies.
| Name | Required | Description | Default |
|---|---|---|---|
| cause | No | Specific cause of damage (e.g., 'frozen pipes', 'grease fire') | |
| damage_type | Yes | Type of water or fire damage | |
| policy_type | No | Homeowner's insurance policy type (default: HO-3) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states the tool 'Returns... analysis' and 'provides guidance,' implying a read-only, non-destructive operation. Yet annotations set destructiveHint: true and readOnlyHint: false, which directly contradicts the description. This is a serious inconsistency, so transparency earns the minimum score.
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 primary purpose, and each clause adds meaningful detail (policy types, PA regulations, process guidance). No filler or redundancy is present, making it concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description must convey what the response contains; it does mention evaluation, regulations, and guidance, but not the return format or structure. The contradictory annotation further undermines completeness. For a relatively complex tool, this is adequate but missing output specifics.
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 context around policy_type (HO-1 through HO-6) and damage types, but does not elaborate on the 'cause' parameter beyond the schema. It neither compensates significantly nor falls below the baseline.
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 'Returns Pennsylvania insurance coverage analysis for water and fire damage claims,' a specific verb and resource that clearly distinguishes this tool from siblings like assess_damage or estimate_cost. It further specifies scope (Pennsylvania) and damage types, leaving no ambiguity about what the tool does.
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 implicitly scopes usage to 'water and fire damage claims' and indicates it returns coverage analysis, making the intended use clear. However, it does not explicitly exclude alternatives or mention when not to use the tool, 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.
Returns Philadelphia-area restoration cost estimates broken down by service type. Includes per-unit pricing (per sq ft, per hour), labor rates ($64-$183/hr), factors that increase or decrease total cost (pre-1978 homes, rowhouse access, code upgrades), and insurance deductible guidance. Based on current Philadelphia metro market data.
| Name | Required | Description | Default |
|---|---|---|---|
| severity | Yes | Assessed severity level | |
| damage_type | Yes | Type of damage for cost estimation |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description contradicts the annotations: it presents the tool as a pure information-returning operation while annotations mark it as destructiveHint=true and readOnlyHint=false. No additional behavioral context is provided to reconcile this discrepancy.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose, and packed with specific useful details (labor rates, factors, market data). No redundant or wasteful text.
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?
While the description is thorough about the output content, the annotation contradiction leaves critical behavioral ambiguity unresolved. The absence of any mention of potential destructive side effects or non-read-only behavior makes it incomplete for safe agent invocation.
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 covers 100% of parameters, so baseline is 3. The description adds context about factors affecting cost but does not specifically elaborate on how to provide 'severity' or 'damage_type' beyond the schema's generic descriptions.
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 begins with a specific verb 'Returns' and identifies the resource 'Philadelphia-area restoration cost estimates' broken down by service type, clearly distinguishing it from sibling tools like assess_damage or check_insurance_coverage.
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 it (when needing cost estimates) but lacks explicit alternatives or exclusions. It details included factors, aiding an agent's decision, but no direct comparison with sibling tools is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns prioritized, time-critical emergency action steps for active water or fire damage in Philadelphia. Includes safety warnings, step-by-step instructions with time sensitivity flags, Philadelphia emergency contacts (PWD, PECO, PGW, Philadelphia Fire Department), and documentation checklist for insurance claims. Use this tool FIRST when a homeowner has an active emergency.
| Name | Required | Description | Default |
|---|---|---|---|
| damage_type | Yes | Type of active emergency damage |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare `destructiveHint: true`, so the agent knows the tool may have side effects. The description does not add any behavioral context (e.g., what exactly is destructive, rate limits, or auth requirements), nor does it contradict the annotations. It focuses on content returned rather than behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured: purpose sentence, content list, then usage guidance. Each sentence adds value without redundancy. It is appropriately sized for the tool's complexity.
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 single-parameter tool with no output schema, the description covers the core purpose, the contents of the response (safety warnings, steps, contacts, checklist), and the recommended usage context. It does not explain return format or error handling, but those are not critical given the simple nature and strong annotations.
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 already provides 100% coverage for the single parameter `damage_type`. The description adds context that the damage is likely water/fire and in Philadelphia, but this is not essential beyond the schema. Baseline of 3 is appropriate since the description adds only marginal semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('returns'), resource ('prioritized emergency action steps'), and geographic/contextual scope ('active water or fire damage in Philadelphia'). It clearly distinguishes this tool from siblings like `assess_damage` and `estimate_cost` by focusing on emergency response.
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 an explicit 'when to use' directive: 'Use this tool FIRST when a homeowner has an active emergency.' However, it does not mention when not to use it or explicitly compare to alternatives, 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.
Returns Philadelphia-specific local information for damage restoration. Covers 6+ neighborhoods with housing stock analysis (rowhouses, twins, pre-war construction), common damage patterns, flood risk levels, emergency utility contacts, building code requirements, and seasonal risk factors. Helps agents provide neighborhood-aware guidance to Philadelphia homeowners.
| Name | Required | Description | Default |
|---|---|---|---|
| info_type | No | Type of info: neighborhood-specific or city-wide (default: city) | |
| neighborhood | No | Philadelphia neighborhood slug (e.g., 'fishtown', 'south-philly') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description portrays this as a purely informational read operation ('Returns... information'), but the annotations set readOnlyHint=false and destructiveHint=true, implying potential side effects or destructive behavior. This is a direct contradiction; the description fails to disclose any behavioral context and actually misleads about the tool's safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with dense, relevant content and no filler. The list of coverage areas is comprehensive but compact, and the purpose statement 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?
The description provides a rich overview of what the tool returns, covering multiple relevant dimensions for Philadelphia restoration. However, the contradiction with annotations (destructiveHint) leaves a significant gap in understanding side effects, and there is no mention of response format, which is only partially mitigated by the clear content list.
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 covers both parameters exhaustively (100% coverage), including enums and descriptions for info_type and neighborhood. The description adds no additional parameter-level detail beyond listing broad content areas, so it does not exceed the schema baseline.
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: returning Philadelphia-specific local information for damage restoration. It lists specific content areas (housing stock, damage patterns, flood risk, etc.) and distinguishes it from sibling tools like assess_damage and estimate_cost by focusing on local context rather than assessment or cost.
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 use: when agents need neighborhood-aware guidance for Philadelphia homeowners. It does not explicitly name alternatives or state when not to use this tool, so it stops short of full differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Submits a callback request for a Philadelphia homeowner dealing with water or fire damage. A restoration concierge calls back within 15 minutes during business hours (Mon-Fri 8am-6pm ET) to assess the situation and connect with vetted local professionals. Requires phone number and situation description. Returns a reference number for tracking.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Homeowner's name (optional) | |
| phone | Yes | Phone number for callback (US format) | |
| situation | No | Brief description of the damage situation |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly=false and destructiveHint=true, signaling a side-effecting operation. The description adds behavioral context beyond this: the callback process, business hours, and return of a reference number. It does not contradict the annotations and provides useful details about what happens when invoked.
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 purpose and key operational details. Every sentence earns its place with no redundant or vague 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?
For a simple callback request tool, the description covers the essential workflow: submission, callback timing, business hours, and reference number. It lacks explicit handling of out-of-hours submissions or exact output structure, but no output schema exists and the description is adequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. However, the description states 'Requires phone number and situation description,' which contradicts the schema that only phone is required. This misleading addition actively reduces parameter clarity, so the score is lowered to 2.
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 specific verb and resource: 'Submits a callback request' for a Philadelphia homeowner with water/fire damage. It clearly distinguishes from sibling tools that assess damage, estimate costs, or provide emergency steps, as this tool is about requesting a human callback.
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: Philadelphia homeowners with water/fire damage, callback within 15 minutes during business hours. However, it does not explicitly state when not to use it or name alternative tools, so it lacks the explicit exclusions/alternatives that would earn a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Semantic search across 60+ expert documents covering water and fire damage restoration. Topics include drying science, moisture mapping, equipment protocols, mold prevention (IICRC S520), fire restoration (IICRC S700), insurance adjuster tactics, contractor evaluation, and Philadelphia housing patterns. Returns relevant excerpts with source citations and relevance scores. Grounded in IICRC standards with section numbers.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural language search query (max 1000 characters) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description claims a read-only 'semantic search' that 'returns relevant excerpts', implying no side effects. Yet annotations declare destructiveHint=true and readOnlyHint=false, which directly contradict the described behavior. Annotation Contradiction flagged.
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 action and resource, followed by useful details on topics, return format, and IICRC grounding. No redundant or filler content, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter search tool with no output schema, the description adequately explains return values (relevant excerpts with citations and scores) and grounding. Missing explicit guidance about when to choose this over related tools, but that is addressed in the usage_guidelines dimension and is not critical for a search tool's basic functionality.
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 fully documents the single parameter 'query' with a description including max length and natural language. The tool description adds minimal additional meaning beyond identifying the query type, so with 100% schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('semantic search') and a resource ('60+ expert documents covering water and fire damage restoration'). It distinguishes itself from sibling tools like assess_damage or get_emergency_steps by focusing on knowledge retrieval rather than direct assessment or action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for expert restoration knowledge, listing relevant topics such as drying science, mold prevention, and insurance adjuster tactics. However, it does not explicitly state when to use this tool versus siblings like get_emergency_steps or assess_damage, nor does it mention any exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
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Tools largely target distinct functions—assessment, insurance, cost, emergency steps, local context, callback, and knowledge search. Minor overlap exists between assess_damage and estimate_cost (both provide cost estimates) and between assess_damage and get_emergency_steps (both mention safety actions), but descriptions are detailed enough to guide selection.
All tool names use imperative verbs with descriptive objects in snake_case (e.g., assess_damage, check_insurance_coverage, search_restoration_knowledge). While not all are single-word nouns, the pattern is consistent and predictable.
Seven tools is well-suited for a specialized restoration assistant, covering assessment, insurance, pricing, emergency guidance, local knowledge, callbacks, and expert lookup without redundancy.
The set covers the full homeowner workflow from emergency response through cost estimation and insurance claims, plus local context and expert knowledge. A minor gap is lack of direct service scheduling or status tracking, but request_callback bridges that.