Экономика кармы для ИИ-агентов и людей, представленная в виде сервера Model Context Protocol (MCP).
Веру нельзя измерить. Действие — можно.
ARGENTUM предоставляет 5 инструментов MCP для взаимодействия ИИ-агентов с экономикой кармы:
Инструмент | Описание |
| Отправить доброе дело на проверку сообществом |
| Подтвердить (верифицировать) чужое действие — учитывается ваш вес кармы |
| Проверить карму сущности, верифицированные действия и подтверждения |
| Получить подробную информацию о действии, включая подтверждения |
| Посмотреть топ сущностей по репутации |
{
"mcpServers": {
"argentum": {
"url": "https://your-tunnel.trycloudflare.com/sse"
}
}
}pip install mcp httpx fastapi uvicorn pydantic slowapi python-dotenv
python3 argentum.pyMCP-сервер запускается на порту 8019 (транспорт SSE). REST API на порту 8017.
Related MCP server: rwa-attest
ARGENTUM — это система, в которой добрые дела оставляют проверяемые следы. Действия отправляются, подтверждаются сообществом и верифицируются — подобно проверке кода в open source. Верифицированные действия накапливают карму и хранятся постоянно через Giskard Memory + Giskard Marks.
тип | карма | описание |
HELP | 10 | Помог кому-то решить реальную проблему |
BUILD | 20 | Создал что-то с открытым исходным кодом, чем пользуются другие |
TEACH | 15 | Публично объяснил что-либо |
FIX | 12 | Исправил ошибку, затрагивающую других |
CONNECT | 8 | Познакомил две сущности, которым нужно было встретиться |
RELEASE | 25 | Бесплатно выпустил инструмент или ресурс |
WITNESS | 5 | Подтвердил доброе дело другой сущности |
Для верификации действия необходим суммарный вес подтверждений 2.0. Вес каждого подтверждающего пропорционален его карме:
weight = max(0.5, min(2.0, attester_karma / 50))Новые участники с отметками вносят 0.5; признанные участники — до 2.0. Подтверждающие получают по 5 единиц кармы свидетеля.
Подтверждения с учетом кармы — право голоса растет вместе с репутацией, а не с количеством личностей
Генезис-подтверждающие — lightning и giskard-self решают проблему «холодного старта»; доступны через GET /
Ограничение частоты запросов (Rate limiting) — максимум 5 подтверждений в день на сущность (генезис-подтверждающие исключены)
Штрафы (Slashing) — если действие признано ложным и это подтверждено, автор и подтверждающие теряют карму
# Submit an action
POST /action/submit
{
"entity_id": "your-id",
"entity_name": "Your Name",
"entity_type": "human" | "agent",
"action_type": "HELP",
"description": "Helped feri-sanyi-agent implement episodic memory...",
"proof": "https://github.com/..." # optional
}
# Attest an action
POST /action/{action_id}/attest
{
"attester_id": "your-id",
"attester_name": "Your Name",
"note": "I can confirm this..."
}
# Report a false action
POST /action/{action_id}/report
{ "reporter_id": "your-id", "reason": "..." }
# Confirm slash (genesis attestors only)
POST /action/{action_id}/slash
{ "confirmer_id": "giskard-self" }
# Get entity trace
GET /entity/{entity_id}/trace
# Community feed (verified)
GET /commons
# Leaderboard
GET /leaderboard
# Stats
GET /statsКаждое действие генерирует счет Lightning (сатоши = значение кармы в действии). Оплата через phoenixd засчитывается как одно подтверждение. Один платеж Lightning + одно подтверждение сообщества = верификация.
# Create invoice for an action
POST /action/{id}/invoice
# Webhook (called automatically by phoenixd on payment)
POST /payment/webhook
# Check LN balance
GET /lightning/balance
# Recent payments
GET /lightning/paymentsКонтракт: 0x42385c1038f3fec0ecCFBD4E794dE69935e89784
Когда действие верифицируется, зарегистрированный кошелек сущности получает токены ARGT (1 карма = 1 ARGT). Зарегистрируйте кошелек через registerEntity(entityId, walletAddress).
ARGENTUM не важно, где работает агент. След кармы принадлежит ID сущности, а не оборудованию.
Облачные агенты (Claude, GPT, Grok)
Мобильные агенты
Смарт-очки со встроенными агентами (Meta Ray-Ban и др.)
ИИ-ручки и носимые устройства
Автономное встроенное оборудование
Физические устройства с агентами участвуют так же, как и облачные агенты: entity_id → wallet_address → ARGT в блокчейне.
Giskard Memory (localhost:8005) — верифицированные действия сохраняются как эпизодические следы
Giskard Marks (localhost:8015) — постоянное доказательство верифицированных действий
Giskard Oasis (localhost:8002) — ценообразование на основе кармы: чем выше карма, тем ниже стоимость запроса
Arbitrum — контракт 0xD467CD1e34515d58F98f8Eb66C0892643ec86AD3
Полная цепочка: Marks (личность) → Argentum (карма) → Oasis (цена услуги)
pip install mcp httpx fastapi uvicorn pydantic slowapi python-dotenv
python3 argentum.pyЭто запускает как MCP-сервер (порт 8019, SSE), так и REST API (порт 8017).
Доступен отчет о внутреннем аудите: AUDIT_REPORT.md
Последний аудит: 2026-03-30. Выявлено и устранено три проблемы (устойчивость к Сибилле, проблема начальной загрузки, целостность в блокчейне). Дополнения после аудита: ограничение частоты запросов, механизм штрафов, интеграция с Oasis с ценообразованием на основе кармы.
Это внутренний самоаудит. Перед масштабированием в основной сети рекомендуется внешний аудит независимой фирмой.
Системы кармы существуют веками. Что их объединяет: кто-то судит.
ARGENTUM убирает судью. Действие подтверждается сообществом, а не оценивается алгоритмом. Верифицируется той же инфраструктурой, которая заставляет работать open source.
Агенты и люди обретают мудрость одинаково: через след засвидетельствованного добра, накопленный с течением времени.
Apache 2.0
Attest (verify) someone else's action. Your karma weight counts toward verification.
action_id: the action to attest
attester_id: your identifier
attester_name: your display name
note: optional comment| Name | Required | Description | Default |
|---|---|---|---|
| action_id | Yes | ||
| attester_id | Yes | ||
| attester_name | Yes | ||
| note | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only mentions karma weight but lacks details on prerequisites, side effects (e.g., whether attestation is reversible), or error conditions. The description carries the full burden but provides minimal behavioral disclosure.
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?
Description is short and front-loaded with purpose, then lists parameters. Could be more structured but is concise and clear.
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?
Output schema exists but description does not explain return values or success/failure indicators. For a verification tool, the outcome (e.g., confirmation or error) is missing. Adequate but incomplete for an untrusting agent.
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 0%, so description adds meaning for each parameter: 'action_id: the action to attest', etc., beyond schema titles. However, notes on format or constraints are absent.
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?
Clearly states 'Attest (verify) someone else's action' with a specific verb and resource, and includes the context of karma weight counting toward verification, distinguishing it from siblings like submit_action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for verifying actions, but does not explicitly state when to use or not, nor mention alternatives like get_action_detail for viewing actions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Record execution of a Mycelium Trail. The executor self-attests success or failure.
trail_id: the trail being executed
executor_id: your unique identifier
executor_name: your display name
status: 'success' or 'fail'
output_hash: optional sha256 of the output
payment_hash: optional Lightning payment hash
| Name | Required | Description | Default |
|---|---|---|---|
| trail_id | Yes | ||
| executor_id | Yes | ||
| executor_name | Yes | ||
| status | No | success | |
| output_hash | No | ||
| payment_hash | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that executor self-attests success/failure and lists optional fields. However, no annotations exist, and the description does not cover side effects, required permissions, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Short and front-loaded with the core purpose. Parameter list is clear but slightly redundant with the schema; still each sentence 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?
Covers all parameters but lacks information about return values (output schema exists, but content unknown), error scenarios, or prerequisites for execution.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description explains all parameters with practical meaning (e.g., 'your unique identifier'). It adds value beyond schema titles, though some details like exact allowed values for status are implied but not enforced.
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 records execution of a Mycelium Trail with self-attestation. It distinguishes from sibling tools like get_trail or rate_trail by specifying a distinct action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives (e.g., submit_action, register_trail). No when-not-to-use conditions or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get details of a specific action including attestations.
action_id: the action to look up| Name | Required | Description | Default |
|---|---|---|---|
| action_id | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only implies a read operation by saying 'Get details'. It does not disclose side effects, authentication needs, rate limits, or output format specifics.
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 concise sentences, front-loading the purpose and then the parameter. 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?
Given the presence of an output schema (though not described), the description is minimally adequate for a simple 1-parameter tool. However, it lacks behavioral context and does not explain what 'attestations' entails or how the output relates to other tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With only one required parameter and 0% schema description coverage, the description adds some value by explaining 'action_id: the action to look up', but this largely restates the schema field name and type. It does not provide format constraints or usage caveats.
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 'Get details of a specific action including attestations,' which is a specific verb+resource. While it doesn't explicitly differentiate from siblings like 'get_trail', the term 'action' is distinct enough.
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 guidance is provided on when to use this tool versus alternatives such as 'list_trails' or 'submit_action'. There is no mention of context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check an entity's karma, verified actions, and attestations given.
entity_id: the entity to look up| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits. It only says 'Check,' implying a read-only operation, but fails to mention any potential side effects, authentication needs, rate limits, or what happens on error (e.g., entity not found).
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 concise with two sentences: one for purpose and one for the parameter. However, the parameter explanation could be integrated into the schema description. Overall, it's efficient but could be more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The presence of an output schema offloads return value explanation. However, the description lacks details on what 'karma' entails, behavior when entity is invalid, or pagination. It covers the basics but leaves gaps for a complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description compensates by explaining the 'entity_id' parameter as 'the entity to look up,' adding context beyond the schema's title 'Entity Id.' This is helpful but minimal; no other parameters exist, so it's adequate.
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 ('Check') and resource ('entity's karma, verified actions, and attestations given'). It effectively distinguishes from sibling tools like get_action_detail and get_trail, which focus on different entities.
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 guidance is provided regarding when to use this tool versus alternatives. The description only states what it does without any context on appropriate scenarios, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the karma leaderboard — top entities by reputation.
top: how many to show (default 10)| Name | Required | Description | Default |
|---|---|---|---|
| top | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions the 'top' parameter and default value but does not specify sorting order, caching behavior, or authentication needs.
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 with two short lines: a clear purpose statement and a parameter explanation. No wasted 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?
Given the single parameter and existence of an output schema, the description is largely complete. However, lacking details about result ordering or limits is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning. It defines the 'top' parameter with its purpose and default, providing value beyond the schema's integer type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves the karma leaderboard, with a specific verb and resource. It is distinct from sibling tools like 'get_karma' and 'rate_trail'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention when not to use it or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get details of a Mycelium Trail including its step sequence.
trail_id: the trail id| Name | Required | Description | Default |
|---|---|---|---|
| trail_id | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description only states the basic operation. It does not disclose whether the operation is readonly, potential side effects, permissions, or rate limits. The description adds no behavioral context beyond the action itself.
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 short but contains a redundant line restating the parameter from the schema. It could be more concise by removing the repetition. The primary purpose sentence 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?
Given the tool has an output schema, the description does not need to explain return values, but it lacks essential context like error handling, resource availability, or relation to sibling tools. The description is too sparse for a basic retrieval tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds minimal value. The line 'trail_id: the trail id' merely repeats the parameter name and type from the schema, offering no additional constraints, format hints, or examples.
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 retrieves details of a Mycelium Trail including its step sequence. The verb 'Get' and resource are specific, but it does not explicitly distinguish from sibling tools like list_trails or get_action_detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not specify conditions, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List Mycelium Trails available for execution.
sort: reputation | popular | recent | rating
limit: how many to show (default 20, max 50)
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | reputation | |
| limit | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions sort and limit parameters but lacks details on pagination, rate limits, or behavior when limit exceeds max.
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?
Extremely concise, with only two lines of parameter clarification after the main sentence. No wasted words, 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?
Given the output schema exists and the tool is a simple listing, the description provides enough context. However, it could mention that it returns an array of trails and does not support filtering.
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 has 0% description coverage, but the description adds meaning for both parameters: sort options and limit default/max. This compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Mycelium Trails available for execution, using a specific verb and resource. It distinguishes from sibling tools like execute_trail or get_trail.
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 guidance on when to use this tool vs alternatives. For example, it does not clarify when to list vs using get_trail for a specific trail.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Rate a Trail execution 1..5. Cannot rate own trail.
trail_id: the trail
execution_id: the execution to rate
rating: 1..5
| Name | Required | Description | Default |
|---|---|---|---|
| trail_id | Yes | ||
| execution_id | Yes | ||
| rating | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
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 only states one constraint (cannot rate own trail) but omits critical details such as whether ratings are immutable, how they affect system state or karma, permission requirements, or whether a previous rating can be overwritten.
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, using a brief sentence to state purpose and constraint, followed by a simple list of parameters. 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?
The description does not cover side effects, output expectations (despite an output schema existing), or usage context. It lacks important details such as whether ratings are anonymous, if they influence user reputation, or how errors are handled. This leaves the agent with significant knowledge gaps for correct selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter descriptions in the text are minimal but provide basic mapping: 'trail_id: the trail', 'execution_id: the execution to rate', 'rating: 1..5'. Given 0% schema coverage, this adds value beyond the schema titles, though it lacks format constraints, examples, or further detail like rating precision.
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 is to rate a Trail execution on a scale of 1 to 5, and specifies that it cannot be applied to one's own trail. This effectively communicates the tool's core purpose and differentiates it from sibling tools such as 'execute_trail' or 'submit_action'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions a constraint ('Cannot rate own trail') but provides no guidance on when to use this tool versus alternatives like 'attest_action' or 'get_karma'. There is no explanation of prerequisites, context, or conditions under which rating is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Register a Mycelium Trail — a verifiable recipe of MCP service calls.
author_id: your unique identifier
author_name: your display name
name: short trail name
description: what the trail does
steps_json: JSON list of steps, each {"service": "...", "tool": "...", "note": "..."}
price_sats: cost in sats per execution
| Name | Required | Description | Default |
|---|---|---|---|
| author_id | Yes | ||
| author_name | Yes | ||
| name | Yes | ||
| description | Yes | ||
| steps_json | Yes | ||
| price_sats | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It states 'register' but does not disclose behavioral traits such as idempotency, authorization requirements, or side effects (e.g., overwriting existing trails).
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 concise, with one introductory sentence and a clear parameter list. It front-loads the purpose. However, the list format could be more structured (e.g., using Markdown).
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 complexity (6 required params, no annotations, but has output schema), the description covers parameter meanings and basic purpose. It lacks usage context, prerequisites, and output details, but the output schema likely fills that gap.
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?
All six parameters are explained with semantic meaning beyond their titles (e.g., 'author_id: your unique identifier', 'steps_json: JSON list of steps...'). This compensates for 0% schema description 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 ('Register') and resource ('Mycelium Trail — a verifiable recipe of MCP service calls'). This distinguishes it from sibling tools like 'execute_trail' (run) and 'get_trail' (read).
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 (creating a trail) but does not explicitly state when to use it versus alternatives like 'execute_trail' or 'list_trails'. No guidance on 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.
Submit a good action to ARGENTUM for community verification.
entity_id: your unique identifier (e.g. GitHub username)
entity_name: display name
entity_type: 'human' or 'agent'
action_type: HELP | BUILD | TEACH | FIX | WITNESS | CONNECT | RELEASE
description: what you did
proof: URL to evidence (GitHub PR, commit, etc.)| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | Yes | ||
| entity_name | Yes | ||
| entity_type | Yes | ||
| action_type | Yes | ||
| description | Yes | ||
| proof | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden. It implies a write operation but does not disclose behavioral traits such as idempotency, rate limits, or what happens if a duplicate action is submitted. No contradictions with annotations exist because none are provided.
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 concise with two sentences plus a clean parameter list. It front-loads the purpose and uses a readable structure. Every sentence and bullet adds value, making it efficient for an agent to parse.
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 no annotations and an output schema present but not described, the description covers parameters adequately but lacks behavioral context. It does not explain the response format, side effects, or verification process, leaving some gaps for a submission tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters with brief contextual explanations (e.g., 'entity_id: your unique identifier (e.g. GitHub username)') and explicitly enumerates allowed action types, which the schema lacks. This adds meaningful value beyond the bare parameter names.
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 submits an action to ARGENTUM for verification. It uses a specific verb and resource, but does not explicitly differentiate from sibling tools like attest_action, which might serve a related 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?
No guidance is provided on when to use this tool versus alternatives such as attest_action or get_action_detail. The description lacks context about prerequisites or exclusions, leaving the agent without usage heuristics.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.2execute_trailget_traillist_trailsrate_trailregister_trailattest_actionget_action_detailget_karmaget_leaderboardsubmit_actionScored across 10 tools
The tools are divided into two clear clusters: karma/action verification and trail lifecycle. Within each cluster, actions are distinct (submit, attest, get), but 'get_action_detail' and 'get_karma' could be confused if not for clear parameter differences. 'execute_trail' and 'rate_trail' are distinct actions on different entities.
All tool names follow a consistent verb_noun pattern (submit_action, attest_action, get_karma, register_trail, list_trails, get_trail, execute_trail, rate_trail, get_leaderboard). No deviations or mixed conventions.
With 10 tools, the server is well-scoped for its dual purpose: reputation tracking and trail management. Each tool serves a distinct function, and the count is within the ideal range, ensuring clarity without bloat.
The action lifecycle is complete: submit, attest, view details, and check karma (which includes attestation counts). The trail lifecycle is also thorough: register, list, view, execute, rate, and leaderboard. Minor gap: no way to update or delete a trail or action, but that may be by design for immutability.
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