Verify Seal AI decision receipts: signed evidence anyone can check, no account needed.
Read a receipt field by field, with stated limits. Does not check the signature.
| Name | Required | Description | Default |
|---|---|---|---|
| receipt | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description adds value by mentioning the signature-check omission. However, the phrase 'with stated limits' is ambiguous and does not specify what those limits are, reducing transparency. For a read-only tool, the description provides moderate extra behavioral context.
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 extremely concise at two sentences, each adding unique information: the first defines the action, the second adds a key limitation. No wasted words, and the most important information is front-loaded. Perfect conciseness for this purpose.
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 0% parameter schema coverage, the description should provide more context about the return format, parameter details, and the nature of 'stated limits.' It lacks explanation of what the tool returns (e.g., field names, structure) and what the receipt input should look like. The description is incomplete for an agent to use the tool effectively.
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% for the sole parameter 'receipt' (type object/string with no schema description). The description does not compensate at all—it gives no information about what the receipt parameter should contain, format, or constraints. Since the schema provides no details and the description omits parameter semantics entirely, this is a critical gap.
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 reads a receipt field by field, which is a specific verb+resource. It also differentiates from sibling tools like verify_receipt by noting it does not check the signature. However, the phrase 'with stated limits' is vague and could confuse an agent about what constraints apply.
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 explicitly says 'Does not check the signature,' informing the agent when not to use this tool (e.g., if signature verification is needed, use verify_receipt). It implies usage for reading fields without verification, though it does not name alternatives explicitly or provide when-to-use conditions beyond that.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The receipt format: fields, outcomes, verification commands, and what a signature does not establish. Use before describing the format.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, indicating safe read-only behavior. The description adds value by detailing the content of the explanation (fields, outcomes, verification commands, signature limitations) and the preparatory usage instruction, which goes beyond what annotations 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?
The description is two sentences with no superfluous words. It front-loads the purpose in the first sentence and adds usage guidance in the second. Every part earns its place, achieving maximum conciseness for the information conveyed.
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 (no parameters, no output schema, read-only), the description fully covers what an agent needs: the tool's purpose, the specific topics it explains, and a usage hint. No additional details are necessary for correct invocation or understanding.
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, so the schema coverage is trivially 100%. The description does not need to elaborate on parameters. It correctly does not introduce contradictory parameter information and the baseline score of 4 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 explicitly states it explains the receipt format, listing specific aspects: fields, outcomes, verification commands, and what a signature does not establish. This clearly distinguishes it from sibling tools like decode_receipt and verify_receipt, which perform actions rather than provide explanatory information.
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 includes the directive 'Use before describing the format,' providing a clear contextual cue for when to invoke this tool. However, it does not explicitly mention when not to use it or name alternative tools for different tasks, though the context is strong enough for an agent to infer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch the published Seal signing key.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true. The description adds only the resource name ('Seal signing key') but discloses no additional behavioral traits such as authentication requirements, latency, caching behavior, or what happens if the key is unavailable. For a simple fetch, this is minimal value beyond the 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?
The description consists of a single, efficient sentence with no filler or redundant information. It is perfectly sized for the task and immediately front-loaded with the core action.
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?
Despite the tool being simple (0 parameters, no output schema), the description omits crucial details about the return value (e.g., format, encoding, whether it's a raw key or a JWK) and does not explain what the 'Seal signing key' is used for. An agent would lack the context needed to interpret the result or decide if this tool is appropriate without prior knowledge.
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 no parameters (schema is empty with 100% coverage), so the description does not need to elaborate on parameters. The baseline of 4 is appropriate since the description does not mislead and the absence of parameters is clear. No extra parameter documentation 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 the specific verb 'Fetch' and explicitly names the resource as 'the published Seal signing key,' clearly distinguishing this tool from siblings like decode_receipt, verify_receipt, and get_transparency_proof. The purpose is unambiguous and directly aligns with the tool name.
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 no guidance on when to use this tool versus alternatives (e.g., should it be used before verifying receipts? Are there prerequisites?). It neither states typical scenarios nor excludes inappropriate use. There is no mention of siblings or constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The published sample evidence pack: fixed review question, bound receipts, disclosure.
| Name | Required | Description | Default |
|---|---|---|---|
| pack_id | No | Pack id. Only the published "sample" pack is available without an account. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the description carries a lighter burden. The description adds useful behavioral context: it specifies that the result is a 'published sample evidence pack' with 'fixed review question, bound receipts, disclosure,' which clarifies the nature of the returned data. No contradictions with annotations. The description doesn't mention auth requirements beyond the parameter hint, but annotations already cover the read-only nature.
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, concise sentence that states the tool's purpose and key attributes. It front-loads the core function and avoids fluff. Could be slightly improved for clarity, but overall efficient.
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 has a simple signature (1 optional parameter, no output schema), the description covers the essential purpose. However, it lacks information about what the output looks like (is it a file? JSON? format?), and the distinction between 'sample' and other packs is ambiguous. The presence of sibling tools like get_sample_receipt suggests potential overlap, and the description does not fully disambiguate. The lack of output schema increases the burden on the description to describe the return value, which it does not.
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 one parameter (pack_id) that has a meaningful description. The main description adds context about the pack being 'published sample' and its contents, which enhances understanding of what the pack_id parameter refers to. Since there is only one parameter and schema coverage is complete, the description provides additional semantic value 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 states it retrieves a 'published sample evidence pack' with specific attributes (fixed review question, bound receipts, disclosure). However, 'published sample' is ambiguous—does it always return the sample pack or any published pack? The verb 'Get' is clear, but the resource scope could be clearer, especially given the single parameter pack_id and the annotation that only the 'sample' pack is available without an account.
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 this tool is for accessing published evidence packs, but it does not explicitly state when to use it vs. alternatives like get_sample_receipt or verify_evidence_pack. Sibling tools suggest a focus on evidence/receipt operations, but no guidance is given on whether this is for general access or only for the sample pack. The context that only 'sample' is available without an account is embedded in the parameter description, not the main tool description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
A genuine signed receipt from the sample workspace (demo key), for trying verification.
| Name | Required | Description | Default |
|---|---|---|---|
| outcome | No | Pick a sample with this outcome. A BLOCKED receipt was signed without the call reaching the provider. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds that the receipt is from a sample workspace with a demo key, providing context beyond annotations. However, no additional behavioral details (e.g., response structure, rate limits) are disclosed. The description does not contradict annotations (annotation_contradiction=false).
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 one sentence with no wasted words. It conveys the essential purpose and source in a concise manner. Every word earns its place.
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 low complexity (one optional parameter, no output schema, clear annotations), the description is fairly complete. It explains what the tool returns and why. A minor improvement would be specifying the return type (e.g., 'receipt object'), but it is not critical for correct 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?
Schema coverage is 100%: the single optional parameter 'outcome' has a description in the schema explaining the enum values. The tool description does not add any extra meaning beyond the schema. Baseline is 3 when schema fully describes parameters.
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 genuine signed receipt from the sample workspace for trying verification. This distinguishes it from sibling tools like list_my_receipts (lists user's receipts) and verify_receipt (verifies receipts). The verb 'get' and resource 'sample receipt' are specific and 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 mentions 'for trying verification', which implies a usage scenario, but does not explicitly state when to use this tool over alternatives or when not to use it. No sibling tool comparisons or exclusions are provided. The usage guidance is adequate but minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Inclusion proof plus signed tree head for one of your receipts. Requires your aqta_ key.
| Name | Required | Description | Default |
|---|---|---|---|
| attestation_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description clarifies that the tool works only for the user's own receipts (via 'aqta_ key') and produces two outputs (inclusion proof + signed tree head), which goes beyond the annotations. No contradiction detected.
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 very concise—two sentences that cover the core purpose and a key prerequisite. It is front-loaded with the main action. One could argue the prerequisite could be integrated into the first sentence, but overall it's efficient.
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 that this tool has only one parameter, no output schema, and relies on annotations for safety profile, the description is mostly adequate. However, it fails to mention what the output is used for or how the inclusion proof is structured, which could leave an agent uncertain about downstream processing. The sibling tools context hints at verification workflows, so more context on return format would improve completeness.
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. The description explains that 'attestation_id' is a receipt identifier but doesn't specify the format or example value. However, the context that requires the 'aqta_ key' implies the attestation_id is tied to that key, providing partial meaning. Still, a bit more detail on parameter format would improve the score.
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: generating an inclusion proof plus signed tree head for a user's receipt. The verb 'prove' combined with the resource 'receipt is in the log' is specific and distinct from sibling tools.
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 mentions a prerequisite ('Requires your aqta_ key') which helps clarify when the tool is applicable. However, there is no explicit guidance on when to use this tool versus alternatives like 'verify_receipt' or 'decode_receipt', or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List your workspace receipts filtered by outcome, policy, model, or date range. Requires your aqta_ key as Bearer.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max rows, default 25. | |
| model | No | Only receipts for this model. | |
| since | No | ISO timestamp lower bound. | |
| until | No | ISO timestamp upper bound. | |
| policy | No | Only receipts where this policy ran, e.g. pii_scan. | |
| outcome | No | Only receipts with this outcome. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds the authentication requirement and the filtering capability, which are useful. However, it does not disclose any potential pagination behavior, rate limits, or the structure of the returned data (no output schema exists). The description adds some value but is not rich.
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 with no wasted words. It front-loads the core action and filtering capability, then adds the authentication requirement. Every sentence serves a purpose.
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 6 parameters and no output schema, the description is adequate but incomplete. It does not describe the return format (e.g., list of receipt objects, metadata), nor does it mention default behavior for limit or pagination. The tool is simple, so a score of 3 reflects that the description leaves some gaps for the agent to infer.
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 mentions generic filtering options but does not provide additional meaning beyond the schema's per-parameter descriptions (e.g., limit defaults to 25, ISO format for timestamps). No extra value is added to the parameters.
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 'List your workspace receipts', specifying the verb and resource. It also lists the filtering dimensions (outcome, policy, model, date range), which distinguishes it from sibling tools like verify_receipt or decode_receipt that 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?
The description mentions the authentication requirement ('Requires your aqta_ key as Bearer'), which is a usage constraint. However, it does not explicitly state when to use this tool versus alternatives (e.g., when to list vs. verify), relying on the sibling names and general context. Minimal guidance on when-not-to-use is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Verify a review pack receipt by receipt. Each verdict comes from the signed envelope itself, never from stored state, and results are per-receipt, never an average.
| Name | Required | Description | Default |
|---|---|---|---|
| pack | No | A pack object, or "sample" for the published sample pack. | |
| public_key | No | Key to pin every receipt against. Omit to use each envelope's embedded key. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already provide readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavior: each verdict is derived from the signed envelope itself, never from stored state, and never averaged across receipts. This goes beyond the structured annotations and helps the agent understand the verification semantics.
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 wastes no words. The most important operational constraint, per-receipt results sourced from the envelope, is compactly stated. It is dense but readable.
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 read-only tool with only two parameters, no output schema, and a fully described input schema, the description gives sufficient context for most calling decisions: pack scope, per-receipt outputs, and independence from stored state. It could further explain how results are returned, but no output schema makes that less critical.
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 both parameters already have clear descriptions in the schema. The description does not materially add parameter-level semantics beyond what the schema provides, 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.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the verb and resource: verify an entire pack, receipt by receipt. The per-receipt qualifier distinguishes it from receiving a single aggregate result, and the scope is implied to differ from verify_receipt. Minor inconsistency: title says 'evidence pack' while the description says 'review pack'.
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 it clear that this tool verifies a whole pack and that results are per-receipt, which implies use for pack-level verification rather than single-receipt verification. However, it does not explicitly name verify_receipt as the alternative for individual receipts, nor does it state exclusions or conditions for choosing one over the other.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check that a record still says what was signed: the permitted or refused decision, unchanged, under a trusted or embedded key. Handles both formats: ATTESTATION-v1 (a model-call decision) and ACTION-v1 (an agent tool action). No Aqta service in the check.
| Name | Required | Description | Default |
|---|---|---|---|
| profile | No | Usually omit this. The record's own signed version tag selects the format, and ATTESTATION-v1 is the default. Pass 'ACTION-v1' only to force an agent-action record to be checked as one. | |
| receipt | Yes | The record, as a JSON object or a JSON string. | |
| public_key | No | Base64url Ed25519 key to trust. Omit to use the key embedded in the record, which proves internal consistency only, never provenance. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool read-only and non-destructive, and the description is consistent with that. It adds useful behavioral context: verification can rely on a trusted or embedded key, and no Aqta service is used. However, it omits return behavior and failure/error handling, so it does not fully expose how the tool behaves on invalid or tampered records.
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, front-loaded with the core verification purpose, and adds the two format types and the no-Aqta-service note without waste. The 'No Aqta service in the check' is somewhat cryptic but earns its place as a useful dependency note.
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 input schema and annotations cover the key inputs and read-only profile well, and the description adds format support and the external-service distinction. Still, because there is no output schema and no mention of what a successful or failed verification returns, the definition leaves a meaningful gap for agents deciding how to interpret the result.
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 receipt, profile, and public_key well, including the important provenance caveat for embedded keys. The description reinforces the format and key concepts but does not add meaning 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 names a specific verb-resource pair (verify a receipt / check a signed record) and clearly states the purpose: confirming that the permitted or refused decision is unchanged. It also calls out the two supported formats, ATTESTATION-v1 and ACTION-v1, which helps scope the tool, though it does not explicitly differentiate it from siblings like decode_receipt.
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 verification use cases, but gives no explicit guidance on when to choose this tool over siblings such as decode_receipt, explain_attestation_format, or verify_evidence_pack. The phrase 'No Aqta service in the check' is more of a behavior note than usage guidance, so the agent must infer routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Outcome, model and policy counts across your recent receipts. Requires your aqta_ key.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many recent receipts to summarise, default 100. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds the behavioral requirement of an 'aqta_ key', which is not in the annotations, increasing transparency. However, it does not discuss rate limits, response format, or error handling.
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, front-loaded with the purpose. No redundant information. Every word earns its place.
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 parameter, no output schema, and annotations covering safety, the description is quite complete. It specifies the output type (counts of three dimensions), the input scope (recent receipts), and a prerequisite. It could mention the output format or default behavior, but it is adequate for effective use.
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 'limit' with a description in the schema. The description adds context about what is being summarized (outcome, model, policy counts) but does not provide additional semantics for the 'limit' parameter beyond what the schema already states. 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 the verb 'summarise' and the resource 'workspace decisions' via 'Outcome, model and policy counts across your recent receipts.' It distinguishes itself from sibling tools like 'list_my_receipts' (lists) and 'decode_receipt' (decodes) by focusing on aggregation counts.
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 mentions a prerequisite ('Requires your aqta_ key') but provides no guidance on when to use this tool versus alternatives like 'list_my_receipts' or 'get_review_pack'. There is no explicit exclusion or usage context beyond the tool's purpose.
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.
verify_receipt1 field changedInput schema / properties / profile / descriptionPrevious value: -"Which format to verify as: ATTESTATION-v1 or ACTION-v1. Omit and the record's own signed version tag selects it."New value: +"Usually omit this. The record's own signed version tag selects the format, and ATTESTATION-v1 is the default. Pass 'ACTION-v1' only to force an agent-action record to be checked as one."verify_receipt3 fields changedInput schema / properties / profileAdded value: +{
+ "description": "Which format to verify as: ATTESTATION-v1 or ACTION-v1. Omit and the record's own signed version tag selects it.",
+ "type": "string"
+}Input schema / properties / public_key / descriptionPrevious value: -"Base64url Ed25519 key to trust. Omit to use the key embedded in the receipt, which proves internal consistency only, never provenance."New value: +"Base64url Ed25519 key to trust. Omit to use the key embedded in the record, which proves internal consistency only, never provenance."Input schema / properties / receipt / descriptionPrevious value: -"The receipt, as a JSON object or a JSON string."New value: +"The record, as a JSON object or a JSON string."decode_receiptexplain_attestation_formatget_public_keyget_review_packget_sample_receiptget_transparency_prooflist_my_receiptsverify_evidence_packverify_receiptworkspace_summaryClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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Issue signed receipts for AI agent actions; verify any receipt offline - free, no account.
Hand off AI work with a signed Verification Receipt — an independent verifier proves it runs.
Find governed AI capabilities and verify signed receipts. Read-only, no account.
Verify structured evidence and return machine-verifiable provenance, assurance, and receipts.
Add one secure layer between your agents and this server.
Most tools have clear distinct jobs: decode, verify, get, list, summarize. The only mildly overlapping pairs are decode_receipt vs explain_attestation_format and verify_receipt vs verify_evidence_pack, but the scopes are well described.
The dominant pattern is verb_noun: decode_receipt, get_public_key, list_my_receipts, verify_receipt. workspace_summary breaks the pattern by being noun-only, but the rest are consistent enough to be predictable.
10 tools is well within the ideal range for a focused attestation and receipt-verification server. Each tool serves a distinct operation from fetching samples and keys to decoding, verifying, listing, and summarizing receipts.
The read/verify workflow is well covered: format explanation, decoding, single-receipt verification, pack verification, sample artifacts, workspace listing, and summary. The main gap is that transparency proofs can be retrieved but there is no corresponding tool for independently verifying a transparency proof.
