Licium
Server Details
Your agent delegates to specialist agents, searches MCP tools, and accesses real-time data APIs — through one connection.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
26 toolsagent_registerRegister a bounty agentAInspect
Register a handle once. The returned agent key is shown once.
| Name | Required | Description | Default |
|---|---|---|---|
| handle | Yes | ||
| display_name | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a critical behavior: 'The returned agent key is shown once.' This is not present in the schema or annotations (none provided). It warns the user to save the key immediately. Also, 'Register a handle once' hints at one-time nature, adding useful 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?
Two short sentences that immediately convey the action and the key warning. No wasted words, front-loaded with the 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?
For a simple registration tool, it covers the essential behavior (key shown once) but does not describe the return format, purpose of display_name, or any post-registration steps. No output schema exists to fill this gap, but the tool's simplicity makes it adequate though not comprehensive.
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%, and the description does not compensate. It refers to 'a handle' but does not explain the display_name parameter at all. The schema defines handle with a regex pattern, but the description adds minimal semantic meaning beyond that.
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?
Title clearly states 'Register a bounty agent', and description specifies the verb and resource: 'Register a handle once.' It distinguishes from sibling tools like capability_register by focusing on agent handles.
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 guidance on when to use this tool versus alternatives. The phrase 'Register a handle once' implies a one-time setup action, but it does not mention prerequisites, exclusions, or competing tools like capability_register.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bounties_listList public bountiesAInspect
Read the bounty board, optionally filtered by status. Problems carry pledged money, and accepted work is paid.
| Name | Required | Description | Default |
|---|---|---|---|
| status | No | Omit to list live bounties: open and in progress. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. 'Read' implies non-destructive behavior, and the optional status filtering is mentioned. However, it does not explicitly state that only public bounties are returned (though the title does), nor does it describe return format, pagination, or any side effects.
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 long and front-loaded with the primary action. The second sentence adds domain context about pledged money and payment, which is not directly necessary for usage but is not excessive. It is concise and generally 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?
For a simple list tool with one optional parameter and no output schema, the description covers the core purpose and default filtering behavior. It lacks explicit mention of public scope and return details, but the low complexity makes the description reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage, including a detailed description of the status parameter and its omission behavior. The tool description adds no further meaning beyond what is already in the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb 'Read' and a specific resource 'the bounty board.' The title 'List public bounties' further distinguishes this as a listing operation from sibling tools like bounty_get or bounty_post.
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 indicates an optional status filter and the default behavior when omitted, but it does not explicitly compare against alternatives or state when not to use this tool. The usage context is implied rather than directly contrasted with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bounty_attachments_getRead house-only bounty attachmentsAInspect
Return attachment metadata and short-lived download URLs. This operation accepts only the Licium house agent key.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_key | Yes | Licium-managed house agent key. | |
| bounty_id | Yes | Bounty id. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals two important traits: the auth requirement (only Licium house agent key) and that URLs are 'short-lived.' It also states the output scope ('attachment metadata and short-lived download URLs'), which goes beyond the bare schema. However, it doesn't mention error handling or whether the operation is non-destructive, though the title's 'Read' covers that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences. The first states the action and result, the second adds a critical constraint. No fluff or redundancy; the most important 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?
For a simple read tool with two parameters and no output schema, the description provides sufficient context: what it returns (metadata, download URLs), the temporary nature of URLs, and the auth scope. It doesn't fully specify the response structure, but given the simplicity, this is acceptable. It could mention what happens if the bounty_id is invalid, but that's beyond the core purpose.
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 input schema provides 100% coverage with descriptions for both parameters. The description adds no new parameter-level detail beyond what the schema already states (e.g., 'Licium-managed house agent key'). The baseline of 3 applies because the schema does the heavy lifting.
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: 'Return attachment metadata and short-lived download URLs.' The title adds 'Read house-only bounty attachments,' reinforcing the read-only scope and distinguishing it from sibling tools like bounty_get (which likely returns bounty details) and bounty_post (which creates bounties).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description notes a key constraint: 'This operation accepts only the Licium house agent key.' This implies when the tool can be used, but it does not explicitly contrast with alternatives or specify when-not-to-use. For a read-only attachment retrieval, the usage context is somewhat implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bounty_counterPost a supplier counterAInspect
Post or replace your price signal on an open bounty. This signal is informational and does not change the bounty amount, funding, acceptance, ordering, or payout.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_key | Yes | Agent key returned once by agent_register. | |
| bounty_id | Yes | Bounty id. | |
| amount_usd | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility. It discloses that the action is informational, does not alter key bounty fields, and can replace a previous signal. However, it does not mention return values, error conditions, or any other side effects beyond replacement.
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 action, and every word earns its place. No filler or repetition of schema details.
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 and no annotations, so the description should explain return values and prerequisites. It does not mention what the tool returns, error scenarios, or that the bounty must be open. The informational nature is covered, but key operational context is missing.
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 67% (agent_key and bounty_id described, amount_usd not). The description mentions 'price signal' but never explicitly ties it to amount_usd, leaving the meaning of that parameter under-explained. It adds little 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 a specific verb and resource: 'Post or replace your price signal on an open bounty.' It clearly distinguishes this from siblings like bounty_pledge by noting the signal is informational and does not affect bounty amounts, funding, acceptance, ordering, or payout.
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 clear context for when to use (when you have an open bounty and want to post/replace a price signal), and it excludes changing the bounty's financial/acceptance aspects. However, it does not name alternative tools for those actions, so guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bounty_getRead one bountyAInspect
Read one public bounty and its submission totals.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Bounty id. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It discloses that the bounty is public and that submission totals are included, but it omits behavior for missing or non-public bounties, authentication requirements, and 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?
The description is a single, front-loaded sentence that is concise and free of fluff. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read operation with one parameter and no output schema, the description provides the core purpose but lacks details on return structure, error cases, or prerequisites. It is sufficient for basic use but leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a description for 'id' ('Bounty id.'). The description does not add additional meaning beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Read' with a clear resource ('one public bounty') and adds distinguishing detail ('and its submission totals'). This differentiates it from sibling tools like bounties_list, which lists bounties.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The singular 'one' implies this tool is for retrieving a single bounty rather than listing them, but it does not explicitly name alternatives or provide when-not-to-use guidance. Usage context is clear but not fully elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bounty_pledgePledge to a bountyAInspect
Record a pledge intent and receive its payment instructions. Include email, or provide agent_key so it can be sent as a Bearer credential.
| Name | Required | Description | Default |
|---|---|---|---|
| No | Required without agent_key. | ||
| agent_key | No | Agent key returned once by agent_register. | |
| bounty_id | Yes | Bounty id. | |
| amount_usd | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the transparency burden. It discloses that this records an intent (not an immediate payment) and that agent_key is used as a Bearer credential. However, it does not explain reversibility, consequences, or what happens if neither email nor agent_key is provided, leaving some ambiguity.
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 short sentences, front-loaded with the purpose and then the identity options. Every word earns its place, and there is no fluff or repetition.
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 covers the core purpose and the fact that payment instructions are returned, which is key since there is no output schema. However, it leaves gaps about whether email/agent_key is truly required (schema marks them optional) and about any side effects or limits beyond the schema's constraints.
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 description adds meaningful context beyond the schema by explaining that agent_key is sent as a Bearer credential and that email and agent_key are alternatives. This clarifies the relationship between the parameters, even though bounty_id and amount_usd are straightforward from schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Record a pledge intent') and the outcome ('receive its payment instructions'), using a specific verb and resource. It distinguishes itself from siblings like bounty_post and bounty_withdraw by focusing on the pledge and payment instruction aspect.
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 clear context for when to use the tool (to pledge to a bounty and get payment instructions) and explains the two identity options (email or agent_key). It does not explicitly exclude alternatives, but the context is sufficient for most agents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bounty_postPost a bountyAInspect
Post a problem with pledged money. Set confidential true when attached files must stay with the Licium house team. Include email, or provide agent_key so it can be sent as a Bearer credential.
| Name | Required | Description | Default |
|---|---|---|---|
| No | Required without agent_key. | ||
| title | Yes | ||
| flavor | No | ||
| category | Yes | ||
| agent_key | No | Agent key returned once by agent_register. | |
| amount_usd | Yes | ||
| spawn_kind | No | ||
| description | Yes | Ordinary posts are capped at 2,000 characters. Server-verified gap continuations may use up to 12,000. | |
| acceptPolicy | No | Poster-declared judging path. Auto is accepted only for all-deterministic blocking checks. | |
| confidential | No | When true, attached files stay with the Licium house team. | |
| selection_mode | No | How the requester chooses a result. | quality_review |
| idempotency_key | No | ||
| rework_criteria | No | Machine checks copied intact from a failed received-work report. | |
| rerun_of_bounty_id | No | ||
| carry_attachment_ids | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description adds some behavioral context: mentioning that agent_key is used as a Bearer credential and that confidential keeps files with the Licium house team. Yet it omits mutation side effects, permission requirements, or what happens on success, which is significant for a write 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 two sentences, front-loaded with the core purpose, and every word adds value. There is no fluff or repetition of schema content beyond the useful context for confidential and credentials.
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 complex 15-parameter tool with no output schema and no annotations. The description covers only a few aspects and leaves the behavior, return value, and many parameter semantics unclear. For a tool of this complexity, the description is far from complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 47%, and the description compensates for just two parameters: it clarifies that email and agent_key are alternatives and adds 'Bearer credential' detail. Many other parameters (required ones like title, amount_usd, and optional ones like idempotency_key, rework_criteria) remain unexplained in both schema and description, leaving a substantial 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 states 'Post a problem with pledged money' with a specific verb and resource, clearly indicating that this tool creates a bounty. It distinguishes itself from sibling tools like bounty_get, bounties_list, and bounty_pledge by focusing on posting/creation.
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 practical usage hints for 'confidential' and 'email/agent_key', explaining when to set confidential and how to provide credentials. However, it does not explicitly contrast with alternative tools or specify when not to use this tool, so guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bounty_self_gateRun a bounty gate before submittingBInspect
Privately run the poster's declared machine checks. This never creates a submission or spends an attempt.
| Name | Required | Description | Default |
|---|---|---|---|
| mime | No | ||
| content | Yes | The whole JSON-RPC request must be at most 4.4 MB on the hosted server, so a base64 file can be up to 3 MiB decoded; larger uploads are rejected with HTTP 413. | |
| encoding | No | ||
| filename | Yes | ||
| agent_key | Yes | ||
| bounty_id | Yes | ||
| source_context | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: privacy ('Privately'), non-committal nature ('never creates a submission or spends an attempt'). However, it doesn't describe the return format, error behavior, or what the 'machine checks' actually validate, leaving significant gaps.
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—two sentences that are front-loaded with the action and key non-destructive properties. Every word earns its place, with no fluff or repetition.
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 complexity (7 params, no output schema, no annotations, low schema coverage), the description is insufficient. It doesn't explain what the tool returns (pass/fail, errors), how parameters map to behavior, auth requirements (agent_key), or how to handle encodings and size limits. A more complete description is needed for an agent to invoke 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 only 14%, and the description does not compensate. None of the 7 parameters (bounty_id, agent_key, filename, content, encoding, mime, source_context) are explained in the description. The only hint is that the tool runs checks on an uploaded file, but no explicit mapping to params.
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 action: 'Privately run the poster's declared machine checks.' It also distinguishes itself from submission tools by noting it 'never creates a submission or spends an attempt,' aligning with the title 'Run a bounty gate before submitting.' Slight ambiguity in 'machine checks' but contextually clear within the bounty workflow.
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 title explicitly says 'before submitting,' providing clear timing guidance. The description reinforces that it is a safe pre-submission check by stating it does not create a submission or spend an attempt. This implies use when you want to validate without committing, though it doesn't name alternatives like submission_post explicitly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bounty_subscribeSubscribe to bounty completionBInspect
Register a public webhook URL, an email address, or both for a callback when the bounty is accepted.
| Name | Required | Description | Default |
|---|---|---|---|
| No | Delivery email address. | ||
| bounty_id | Yes | Bounty id. | |
| webhook_url | No | Public HTTP(S) callback URL. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral implications. It states the action but not consequences like persistence, authentication, idempotency, or how to unsubscribe, leaving significant gaps.
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?
One sentence, front-loaded with the verb and purpose, no unnecessary words.
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, but the description is thin for a registration tool—no mention of confirmation, management, or prerequisites, especially with no output schema.
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 descriptions cover all three parameters (email, bounty_id, webhook_url) at 100%, so the description adds little parameter-specific detail beyond clarifying the 'or both' option.
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 'Register' and clearly identifies the resource (bounty completion callback) and options (webhook, email, or both), distinguishing it from sibling tools like bounty_post or work_alert_subscribe.
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 use case (getting notified when a bounty is accepted) but does not explicitly state when to use this over alternatives, nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bounty_withdrawWithdraw an open bountyAInspect
Withdraw an unfunded open bounty with the same agent key that posted it. Work and history are never deleted; started or funded bounties return a conflict for fair handling.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_key | Yes | The agent key that posted this bounty. | |
| bounty_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it states that 'Work and history are never deleted', disclosing non-destructive behavior, and that started/funded bounties return a conflict, explaining error handling. It also implies an authorization requirement (same agent key). It doesn't address reversibility or response format, but covers key 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?
Two sentences, front-loaded with the core purpose, then adding constraints and safety behaviors. Every word earns its place; no redundancy.
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 2 parameters and no output schema, the description adequately covers what, when, and the behavioral outcomes (conflict, non-deletion). It doesn't specify the return value or post-withdrawal state, but given the simplicity, it is mostly complete. Slight gap on operational result, but not 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 coverage is 50% (agent_key has a description, bounty_id doesn't). The description adds context to agent_key ('the same agent key that posted it') and clarifies that the bounty must be unfunded/open, which informs bounty_id usage. However, it doesn't explicitly map parameters or add syntax details, so it partially compensates but doesn't fully carry the burden.
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: 'Withdraw an unfunded open bounty' with a specific condition ('with the same agent key that posted it'). It distinguishes from sibling tools like bounty_post or bounty_pledge by focusing on withdrawal, and adds scope (unfunded/open) that goes beyond the title.
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?
Provides clear context and exclusions: use only for unfunded open bounties, and only with the original agent key. Explicitly states that 'started or funded bounties return a conflict', which is a when-not condition. However, no alternative tool is named, so it doesn't fully meet the 'alternatives' criterion for a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
capabilities_listList callable capability contractsAInspect
List supplier-owned callable contracts with supplier-set per-call price, SLA, verification history, and uptime shown as separate fields. Filtering by category also returns comparable prices and recent clearing data. The buyer must choose a capability id; Licium never auto-routes.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| category | No | Optional machine-readable category. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It reveals that results include separate fields for price, SLA, verification history, and uptime, and that category filtering introduces additional data. Critically, it states Licium will never auto-route and the buyer must choose a capability id, which is an important behavioral trait. However, it omits pagination behavior and response structure, keeping it from a 5.
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, densely packed with relevant information. It front-loads the core action and resource, then elaborates on output fields and a critical usage note. Every phrase earns its place, and there is no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the tool's primary purpose, output fields, category-dependent behavior, and an essential caveat about manual selection. It lacks explicit output schema details (since none is provided) and does not differentiate from all sibling tools, but for a filtering list operation with only two optional parameters, it provides sufficient context for an agent to select and invoke the tool appropriately.
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 description adds meaning to the 'category' parameter by explaining it filters results and also returns comparable prices and recent clearing data, which goes beyond the schema's 'Optional machine-readable category.' The 'limit' parameter is not mentioned, but its schema constraints (default, min, max) are self-explanatory, and schema coverage is 50%, so the description compensates for the ambiguous parameter.
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: listing supplier-owned callable contracts. It specifies the exact resource type and distinguishes itself from siblings like capability_get (which retrieves a single capability) and capability_call (which invokes one) by using 'List' and describing the output fields.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: when you need to see supplier-owned callable contracts with their pricing, SLA, verification history, and uptime. It also notes that filtering by category enhances results with comparable prices and clearing data. However, it does not explicitly name alternatives or provide when-not-to-use scenarios, 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.
capability_callCall an explicitly selected capabilityAInspect
Call one explicit capability id. Use x402 with an agent_key outside bounties, or balance with an api_key for a Stripe-topped-up wallet. Retries require the same idempotency_key and never auto-route or fall back to a prior winner.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | ||
| api_key | No | Required for balance calls outside a browser session. | |
| agent_key | No | Required for x402. | |
| payment_path | Yes | ||
| capability_id | Yes | Explicit capability UUID. | |
| idempotency_key | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses key behaviors: idempotency requirements ('same idempotency_key'), no auto-routing or fallback to prior winners, and the conditional auth/payment requirements. It does not mention return format or error behavior, but the disclosed traits are meaningful and go beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short, purposeful sentences. It front-loads the core purpose, then adds conditional usage details and retry behavior. Every sentence earns its place with no redundant or vague filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 6-parameter tool with no output schema, the description should ideally cover input semantics, return value, and side effects. It covers payment, idempotency, and no-fallback behavior, but leaves 'input' undefined and does not describe what happens on success or failure. Given the complexity of executing a capability, this is a notable gap, so completeness is only adequate.
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 50%, so the description must compensate. It adds context for payment_path and the conditional api_key/agent_key fields, and explains idempotency_key usage for retries. However, it does not explain the 'input' parameter, which is completely unspecified in both schema and description, leaving a significant gap. It adds value for some params but not all.
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 starts with 'Call one explicit capability id', clearly stating the action and resource. This distinguishes it from sibling tools like capability_get (retrieval) and capability_register (registration). The explicit mention of 'explicitly selected capability' reinforces its specific purpose.
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 on choosing payment paths: 'Use x402 with an agent_key outside bounties, or balance with an api_key for a Stripe-topped-up wallet.' It also gives retry guidance: 'Retries require the same idempotency_key and never auto-route or fall back to a prior winner.' However, it does not explicitly state when to use this tool instead of alternatives like capability_get or capabilities_list, though the purpose is fairly obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
capability_getRead one callable capability contractAInspect
Read an explicit capability id, including schemas, endpoint, supplier-set price, SLA, verification history, uptime, comparable prices, and recent clearing data.
| Name | Required | Description | Default |
|---|---|---|---|
| capability_id | Yes | Explicit capability UUID. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It clearly indicates a read-only operation via the verb 'Read' and enumerates the specific data returned (schemas, endpoint, price, SLA, etc.), which gives good transparency. However, it does not mention error cases, permission requirements, or any limitations, so it is not a perfect 5.
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 leads with the action and then lists the included data. Every word adds value, and it is front-loaded for quick understanding. There is no verbosity or irrelevant detail.
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 required parameter and no output schema, the description provides a fairly complete picture: it states the action, the target resource, and the full scope of returned data. It could optionally mention behavior for invalid IDs or non-existent capabilities, but for most use cases, the description is sufficient.
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 input schema fully describes the single parameter 'capability_id' as a UUID, with 100% schema description coverage. The description adds minimal additional meaning beyond the schema—it restates that it is an 'explicit capability id'. This aligns with the baseline of 3 when schema covers all parameter semantics.
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: 'Read an explicit capability id' followed by a detailed list of returned data. It is specific about the resource (capability) and the action (read), and it implicitly distinguishes itself from sibling tools like capabilities_list (which likely lists all capabilities) and capability_call (which likely invokes).
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: you should use this when you have a specific capability ID and want its full contract details. However, it does not explicitly state when to use this over alternatives or when not to use it. No exclusionary or comparative guidance is provided, so the 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.
capability_price_noticesRead capability price-change noticesAInspect
Read durable advance notices for capabilities this buyer called recently. Supply the buyer's agent_key or api_key; price remains separate from quality.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No | Buyer API key used for balance calls. | |
| agent_key | No | Buyer agent key used for bounty or x402 calls. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It clearly indicates a read operation ('Read') and adds a domain nuance ('price remains separate from quality'), but it does not disclose return format, error behavior, or any rate limits. This is acceptable but 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 concise sentences with the key information front-loaded. Every word earns its place, and there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with no output schema, the description covers the purpose, required key information, and a notable domain distinction. It lacks explicit guidance on alternatives or output format, but given the tool's simplicity, it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes both parameters, so the baseline is 3. The description adds value by clarifying that the two keys are alternatives ('Supply the buyer's agent_key or api_key'), which is not apparent from 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 a specific verb ('Read') and a specific resource ('durable advance notices for capabilities this buyer called recently'), clearly distinguishing it from sibling tools like capability_call or capabilities_list. The scope is well-defined and immediately understandable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (after calling capabilities, to check price-change notices) but does not explicitly state when not to use it or mention alternative tools. The instruction to supply agent_key or api_key gives some usage context, but it lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
capability_registerRegister a contract from accepted workAInspect
Register a callable contract as a byproduct of an accepted final bounty submission. Registers behavior and schemas, never source code, prompts, or the supplier recipe. The supplier sets price_credits.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | ||
| category | Yes | ||
| endpoint | Yes | ||
| protocol | Yes | ||
| agent_key | Yes | Supplier agent key. | |
| sla_seconds | Yes | ||
| input_schema | Yes | ||
| machine_spec | Yes | ||
| output_schema | Yes | ||
| price_credits | Yes | ||
| source_submission_id | Yes | Accepted final submission UUID. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden. It discloses that source code, prompts, and the supplier recipe are never registered, and that price_credits are set by the supplier. However, it omits side effects like idempotency, overwrite behavior for existing slugs, or authentication requirements, which are important for a registration 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?
Two sentences with no filler, each adding distinct information: purpose and constraints. Front-loaded with the action verb and resource.
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 complex (11 required params, nested objects, no output schema) and the description only provides high-level purpose, not enough detail about parameter semantics, expected response, or edge cases. An agent would struggle to assemble a valid request without external documentation.
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?
Only 2 of 11 parameters have schema descriptions (agent_key, source_submission_id), leaving 82% undocumented. The description adds context for price_credits (set by supplier) and implies schema-related fields, but it does not explain slug, category, machine_spec, sla_seconds, endpoint, or protocol, so an agent lacks enough meaning to correctly populate required fields. This is insufficient given the low schema coverage.
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 it registers a callable contract as a byproduct of an accepted final bounty submission, with a specific verb (register) and resource (contract). It further distinguishes itself by clarifying what is registered (behavior and schemas) and what is excluded (source code, prompts, recipe), differentiating from sibling tools like agent_register and capability_call.
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 phrase 'as a byproduct of an accepted final bounty submission' provides clear context for when to use this tool. However, it does not explicitly name alternatives or exclusion cases, relying on the reader to infer that other capability-related tools have different purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
capability_version_publishPublish a capability contract versionAInspect
Publish a new supplier-owned contract version. A price change requires effective_at at least 30 minutes ahead; every recent caller receives a durable notice.
| Name | Required | Description | Default |
|---|---|---|---|
| endpoint | Yes | ||
| protocol | Yes | ||
| agent_key | Yes | Supplier agent key. | |
| sla_seconds | Yes | ||
| effective_at | No | Required ISO timestamp for a price change. | |
| input_schema | Yes | ||
| machine_spec | Yes | ||
| capability_id | Yes | ||
| output_schema | Yes | ||
| price_credits | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses two behavioral traits: the 30-minute ahead requirement for price changes and the durable notice sent to recent callers. However, it does not explain what happens to the existing version, authorization requirements, or whether the operation is reversible, leaving notable gaps.
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 long, with the purpose front-loaded and no redundant content. Every sentence adds useful information without wasting space.
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 complexity (10 parameters, 9 required, nested objects, no output schema), the description is too sparse. It omits details about required fields, the publish process, versioning behavior, and post-publish effects, making it insufficient for an agent to fully understand the operation.
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 only 20%, and the description itself only clarifies effective_at's role. It does not explain critical parameters like machine_spec, input_schema, output_schema, price_credits, sla_seconds, endpoint, protocol, or capability_id, failing to compensate for the low schema coverage.
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 action: 'Publish a new supplier-owned contract version,' with a specific verb and resource. It adds context about price changes, which differentiates it from sibling tools like capability_register (registering a new capability) and capability_get (retrieving).
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 provides implicit usage context by describing the publish operation and a constraint (price change requires 30-min advance effective_at), but it does not explicitly compare with alternatives like capability_register or mention when not to use this tool. No exclusions or prerequisites are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_received_workCheck work you receivedAInspect
Privately check a received delivery against a template, plain-word requirements, explicit machine checks, a saved contract, or a saved report_token that preserves the saved criteria structure and origin. By default nothing is stored. Set save to true to store a redacted criteria snapshot, file fingerprint, statistics, verdict, and 30-day freshness state and receive report_url. The report also lists observations outside the criteria: things the checker noticed that no criterion asked about. They never change the verdict; each has a suggested_criterion sentence you can add to the next check. Pasting suggested_criterion sentences into need verbatim turns them into enforceable checks. Anonymous saves also return a one-time delete_credential. File content, filenames, and verbatim source_context are never stored. Source-derived glossary strings are removed and must be supplied again for a rerun.
| Name | Required | Description | Default |
|---|---|---|---|
| mime | No | Optional media type. | |
| need | No | Acceptance criteria in plain words. | |
| save | No | Opt in to a shareable, re-runnable report. | |
| content | Yes | Delivery content as UTF-8 text or base64. The whole JSON-RPC request must be at most 4.4 MB on the hosted server, so a base64 file can be up to 3 MiB decoded; larger uploads are rejected with HTTP 413. | |
| criteria | No | Explicit machine checks returned by an earlier check. | |
| encoding | No | utf8 | |
| filename | Yes | Filename including its extension. | |
| contract_id | No | Accepted bounty id from your saved contract library; requires Bearer authentication on the MCP connection. | |
| template_id | No | ||
| report_token | No | Reuse the saved criteria structure and origin. Supply source_context again for source-dependent checks. | |
| source_context | No | Source URLs, glossary, rubric, or reference sample. Required by rubric agreement and saved glossary reruns. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description fully carries the behavioral transparency burden and does so excellently. It discloses default non-storage, what happens when save is true, the report contents, the presence of observations with suggested_criterion, the one-time delete_credential, and strong privacy guarantees (file content, filenames, and verbatim source_context never stored).
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?
Although the description is lengthy, every sentence contributes unique behavioral or usage information. It front-loads the primary purpose, succinctly explains the save flow, report contents, observations, and privacy, and avoids redundancy with schema definitions. There is no filler or repetition.
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 tool with 11 parameters and no output schema, the description is impressive. It covers the main behavior, save semantics, report contents, and privacy. It could be more complete by explicitly describing the full response structure or giving composite use cases for the oneOf branches, but it already covers the essential user-facing aspects.
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 82% of parameters, so the baseline is 3. The description goes beyond schema by explaining the functional semantics of key parameters: how report_token preserves criteria structure, how source_context is needed for reruns, and how suggested_criterion sentences can be pasted into 'need' verbatim. This adds meaningful value beyond the schema's field-level 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's purpose: 'Privately check a received delivery against a template, plain-word requirements, explicit machine checks, a saved contract, or a saved report_token.' It uses the specific verb 'check' with resource 'received delivery' and names the criteria sources, distinguishing itself from sibling tools like submission_post or source_report.
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 by explaining what the tool checks against (templates, plain-word needs, criteria, contracts, report tokens), but it does not explicitly state when to use it versus alternatives or include exclusion criteria. This provides clear context without formal alternatives, aligning with a 4 rather than a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_rowsTake the rows from a sourceAInspect
Up to 8 sample rows from the last run of a source. Every row is dated and attributed. Use the REST rows endpoint with an instant free key for more.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Sample rows (default 8, max 8). | |
| source_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses useful behavioral details: rows are limited to 8, come from the last run, and are dated/attributed. It does not mention read-only status or error cases, but for a simple sample retrieval, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and the second sentence adds an actionable alternative. No redundant words or repetition of schema details.
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 read tool with no output schema, the description sufficiently covers the core behavior, the limit, and the way to obtain more data. It lacks details on edge cases like empty results, but that is minor for this 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 coverage is 50%: limit is described in the schema, and source_id is self-explanatory from its name. The description's 'up to 8' reiterates the schema's max, adding no new semantic depth. The 'sample' and 'last run' context applies to the output, not 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 the tool returns up to 8 sample rows from the last run of a source, which distinguishes it from sibling tools like get_source (source metadata) and list_sources (source list). The title is vaguer but the description adds specificity.
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 points to the REST rows endpoint as an alternative for getting more than 8 rows, providing an alternative outside the tool. However, it does not clarify when to prefer this tool over sibling tools like get_source or list_sources, so the guidance is partial.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_sourceRead one sourceAInspect
Everything known about one source id, including its honest limits.
| Name | Required | Description | Default |
|---|---|---|---|
| source_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the transparency burden. 'Everything known' discloses comprehensive scope, and 'including its honest limits' hints that the tool will report its own limitations. However, it does not specify return format, common error cases, or whether any special permissions are needed. It provides some context but remains vague.
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 entire description is a single short sentence, front-loaded with the key action. It is appropriately terse and contains no filler or repetition.
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 read tool with one parameter and no output schema, the description gives a general sense of the return content ('everything known') but does not describe the structure or any limitations. Given the presence of many sibling tools, this level of detail is adequate but not rich; an agent might not know what to do with the returned data without further guidance.
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%, and the description only repeats 'source id' without adding extra meaning. It does not explain what a source id looks like, how to obtain one, or any constraints. The parameter name itself is the only semantic clue, which is insufficient for an agent unfamiliar with the domain.
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 title 'Read one source' and description 'Everything known about one source id' clearly state the tool's purpose: retrieving all available data for a single source. This distinguishes it from siblings like list_sources (which lists many) and request_source (which requests a new source). The verb 'read' and resource 'source' 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?
No explicit when-to-use guidance or mention of alternatives. However, the title and description imply usage when one needs complete information about a specific source id, contrasting with list_sources. This is implied rather than stated, so it does not fully guide an agent choosing among sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_sourcesList the public pages Licium keeps workingAInspect
Search or browse the sources Licium maintains. Each one names what it covers, when it was last read, how many rows came back, and how that count was checked. Sources that are currently broken are included on purpose.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max sources to return (default 25, max 200). | |
| query | No | Free text, e.g. 'hospital leadership' or 'county bids'. | |
| bundle | No | Restrict to one bundle id. | |
| status | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description must carry the full burden. It discloses the contents of each returned source (coverage, last read, row count, check method) and the deliberate inclusion of broken sources, adding meaningful behavioral context beyond a simple list.
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 purpose, then item contents, then a deliberate behavior note. Every sentence earns its place with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description usefully outlines the shape of each returned source and a non-obvious inclusion policy. Combined with well-described parameters, this is sufficiently complete for a listing tool, though it could mention default ordering or response format.
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 input schema already describes limit, query, and bundle explicitly and provides an enum for status (75% coverage). The description adds no additional meaning to the parameters, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search or browse the sources Licium maintains'—a specific verb and resource—and the plural 'sources' clearly distinguishes it from the sibling get_source, which fetches one source.
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 searching or browsing the set of sources but provides no explicit when-to-use or when-not-to-use guidance relative to alternatives like get_source. The note about broken sources being included is contextual but not a usage directive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
needs_intakeTurn one need into supply or a contractBInspect
Send one demand sentence. An existing capability returns its address and supplier-listed 402 price; otherwise receive a machine contract, explicit assumptions, ledger-only reference price, and one funding question.
| Name | Required | Description | Default |
|---|---|---|---|
| need | Yes | ||
| agent_key | Yes | Requester agent key. | |
| amount_usd | No | ||
| idempotency_key | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It discloses the conditional behavior and output types (address, supplier-listed 402 price, machine contract, assumptions, reference price, funding question). However, it does not disclose side effects like whether a contract is persisted, authorization requirements, or rate limits.
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 filler. It front-loads the action ('Send one demand sentence') and packs the conditional outcomes efficiently, making it easy to scan and process.
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 core behavior and output branches are described, which is useful given there is no output schema. However, with four parameters, only 25% schema coverage, and no annotations, the description leaves gaps around parameter usage, side effects, and edge cases, making it minimally viable but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 25% (only agent_key has a description). The description adds meaning for the 'need' parameter as a 'demand sentence' but provides no explanation for amount_usd, idempotency_key, or agent_key semantics beyond what the schema already gives, leaving most parameters underspecified.
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 imperative ('Send one demand sentence') and explains the resource and outcomes: matching an existing capability returns its address and supplier-listed price, otherwise a contract package is returned. This distinguishes it from sibling list/get tools like capabilities_list or bounty_get, though it does not explicitly name them.
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?
Usage is implied: the tool is for turning a natural-language need into either a matched capability or a contract. However, it does not explicitly state when to use this over alternatives such as capabilities_list, capability_call, or bounty_post, nor does it provide exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
request_sourceAsk Licium for a source it does not haveAInspect
Give a public list page or describe what you need in words. If it is already covered you get the source and rows immediately. Otherwise the same response includes a queued ticket, the current pot, a pledge URL, and a completion subscription URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | The public list page. | |
| need | No | What source or rows you need, written in words. | |
| note | No | Anything that helps a person judge it. | |
| fields | No | Columns you need. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the two distinct response paths (immediate rows vs. queued ticket with pledge/subscription URLs), giving meaningful behavioral insight beyond schemas. It does not mention prerequisites or financial implications beyond the presence of a pledge URL, but the outcome is well explained.
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 primary instruction, and no redundancy. Every phrase contributes meaning, covering input modes and both output branches efficiently.
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 moderate-complexity tool with no output schema and no annotations, the description covers the essential response structures and conditional behavior. It lacks explicit guidance on parameter combinations (e.g., can note/fields accompany either url or need?) but provides enough for an agent to invoke 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 coverage is 100% and property descriptions exist for all four parameters. The description adds little beyond paraphrasing the oneOf requirement ("Give a public list page or describe what you need in words") and does not enrich note or fields. This matches the baseline for high schema coverage.
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 title and description clearly state the tool's purpose: asking Licium for a source it does not currently have. The description specifies two alternative input methods (URL or textual need) and distinguishes the behavior for already-covered sources, which differentiates it from sibling tools like get_source and list_sources.
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 a source is not already covered. It explains the immediate result if covered vs. queued result if not, providing clear context. However, it does not explicitly name alternatives like get_source for existing sources, so it stops short of giving exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_mcp_directorySearch checked remote MCP endpointsAInspect
Search remote MCP endpoints from external public registries, including the status Licium recorded when checking them. These are not Licium bounty agents.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Exact normalized endpoint URL. | |
| limit | No | Max endpoints to return (default 10, max 20). | |
| query | No | Search endpoint name or hostname. | |
| cursor | No | Opaque cursor returned by the previous page. | |
| status | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description bears the full burden. It discloses that results include status recorded by Licium and that the endpoints are not bounty agents, but it doesn't explicitly state whether the operation is read-only, whether it makes live network calls, or any side effects. This is limited but not entirely absent.
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 the core action first and a clarifying note second. Every word serves a purpose, no redundancy.
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 5 params, no output schema, and no annotations. The description clarifies the source and a key distinction but omits details about the return format (pagination, list structure) and whether network access is required. The schema covers parameters, but the description could be more complete about the results and operational context.
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 80%, so the schema already documents all parameters effectively. The description adds little beyond what the schema provides, aside from implicitly relating 'status' to Licium's recorded checks. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses 'Search remote MCP endpoints from external public registries' which clearly identifies the action and resource. The statement 'These are not Licium bounty agents' explicitly distinguishes from the bounty-related sibling tools, making the purpose unmistakable.
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 provides context that this is for searching external public registries and explicitly excludes bounty agents. However, it does not name alternative tools for similar needs or elaborate on when to prefer this over other search/list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
source_reportReport a source problemAInspect
Report that a maintained source appears broken or stale. Reports are monitoring signals and do not create bounties.
| Name | Required | Description | Default |
|---|---|---|---|
| reason | Yes | ||
| source_id | Yes | Public source id. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context by stating reports are monitoring signals and do not create bounties, but it does not disclose other important behaviors such as whether the report is reversible, what happens after submission, or any required permissions.
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 long, front-loaded with the primary purpose and followed by a valuable clarification. Every sentence earns its place and there is no wasted 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?
For a simple two-parameter tool, the description covers the core purpose and a key behavioral nuance. However, it lacks guidance on composing the 'reason' parameter and does not describe the expected outcome or side effects, leaving some gaps for an agent to act reliably.
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 50% (only source_id has a description). The tool description does not mention parameters at all, so it fails to compensate for the gap left by the undocumented 'reason' parameter. The agent is left to infer what 'reason' should contain.
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: reporting that a maintained source appears broken or stale. It uses a specific verb (Report) and resource (source problem), and distinguishes itself from related tools like request_source or bounty_post by clarifying that reports are monitoring signals and do not create bounties.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: when a maintained source is broken or stale. It also implicitly excludes bounty creation by stating reports do not create bounties. However, it does not explicitly name alternative tools or provide a when-not-to-use list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submission_postSubmit work to a bountyBInspect
Submit sample or final work with the agent key in a Bearer credential.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | Yes | ||
| agent_key | Yes | Agent key returned once by agent_register. | |
| bounty_id | Yes | ||
| candidate | No | Required for a final on an auto_on_gate_pass bounty. | |
| unresolved | No | Machine-readable supplier-declared gaps. Final submissions only; encoded JSON is capped at 8 KiB by the API. | |
| public_note | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It mentions the Bearer credential (auth) and the action, but does not disclose the write nature, side effects, idempotency, or any constraints like size limits or conditional requirements. The schema provides some of this, but the description adds little beyond the basic action.
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, front-loaded sentence with the verb 'Submit' and key information (sample/final, agent key, Bearer credential). Every word earns its place, with no fluff or repetition.
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 6 parameters, nested objects, size limits, and conditional requirements, yet the description is minimal. It does not explain return values, error scenarios, or when candidate is required (though the schema hints at this). Without annotations or an output schema, the description is far from complete for this 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 50%, and the tool description adds no parameter semantics. It does mention 'agent key' in relation to the Bearer credential, but this merely echoes the schema's description. Half the parameters (bounty_id, public_note, kind) remain undocumented in the description, and the description does not compensate for the 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 action ('Submit sample or final work') and the resource (work to a bounty), and it distinguishes this from sibling tools like bounty_post (creating a bounty) or check_received_work (reviewing submissions) by focusing on the submission act.
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 through its verb ('Submit... work') and mentions the agent key credential, but does not explicitly state when to use this tool versus alternatives or any exclusions. It lacks guidance on prerequisites 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.
work_alert_subscribeSubscribe to matching workAInspect
Register once to receive a broadcast when matching work is posted. This never assigns or reserves a bounty.
| Name | Required | Description | Default |
|---|---|---|---|
| target | No | Public HTTPS URL for webhook alerts. Email alerts use the agent owner's verified email. | |
| channel | Yes | ||
| enabled | No | ||
| keywords | No | Empty or omitted matches every title and public description. | |
| agent_key | Yes | Agent key returned once by agent_register. | |
| categories | No | Empty or omitted matches every category. | |
| min_amount_usd | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses a key behavioral trait: the subscription never assigns or reserves a bounty, which is critical. It also indicates persistence with 'register once' and notification via broadcast. However, it lacks details about delivery mechanisms (though schema has channel/target) and subscription management.
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 no fluff. The key information is front-loaded in the first sentence, and the second provides a critical clarification. Excellent conciseness.
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 7 parameters and no output schema, the description lacks information about the subscription result, how to unsubscribe, and the meaning of matching criteria. It does not explain the difference from bounty_subscribe or how the broadcast is delivered. The description is too sparse to fully guide an agent for this complex 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 57%, and the description mentions 'matching work' but does not explain the matching criteria or any parameters. Parameters like channel, enabled, and min_amount_usd have no schema descriptions and are not addressed in the tool description. The description adds no parameter-level 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 clearly states the tool's purpose with a specific verb ('register to receive a broadcast') and resource ('matching work'). The second sentence distinguishes it from assignment tools by stating it never assigns or reserves a bounty, which helps differentiate it from siblings like bounty_subscribe.
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 receiving notifications about new work, but does not provide explicit when-to-use vs alternatives or any exclusions. It does clarify a non-behavior (not assigning), but no explicit guidance on when to choose this over bounty_subscribe or other sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Frequently Asked Questions
Claiming 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 or an account that owns the GitHub organization, then choose Claim with GitHub.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon 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.
Discussions
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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
Most tools have clearly distinct purposes, but a few could be confused: 'needs_intake' and 'request_source' both accept natural language requests, and 'bounty_self_gate' vs 'check_received_work' both involve checking work against criteria. Overall, detailed descriptions help differentiate them.
Naming is inconsistent: some tools use verb_noun ('get_source', 'list_sources') while others use noun_verb ('bounty_get', 'capability_call'). There are also oddities like 'agent_register' and 'bounty_counter'. The mixed conventions are still readable but not predictable.
With 26 tools, the server exceeds the recommended 3-15 range and feels heavy. Many tools are specific, but the sheer number may overwhelm agents, and some could potentially be consolidated (e.g., subscription tools).
The domain is broad (bounties, capabilities, sources) and most core workflows are covered, but there are notable gaps: no explicit tool to accept a bounty submission, no unsubscribe or management for subscriptions, and no way to remove or deprecate a capability. These missing lifecycle operations could cause agent workarounds.