DJZS Trust MCP
Server Details
Deterministic pre-execution audit for trading agents. PASS/WAIT/FAIL, reproducible verdict_hash.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- SIFR0-dev/djzs-AI
- GitHub Stars
- 3
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Tool Definition Quality
Average 4.3/5 across 3 of 3 tools scored.
Each tool has a clear, distinct purpose: query_agent_trust handles on-chain trust scores, query_pol_certificates retrieves audit certificates, and verify_pm_trade audits prediction market trades. Descriptions explicitly differentiate between the first two.
All tools follow a consistent verb_noun pattern: query_agent_trust, query_pol_certificates, verify_pm_trade. The naming is predictable and clear.
3 tools is on the lower side but appropriate for the focused domain of DJZS trust audits. Each tool is essential and well-scoped.
The set covers core operations: querying trust scores, retrieving audit certificates, and auditing prediction market trades. Minor gaps exist (e.g., no tool for listing agents or managing certificates), but the main workflows are supported.
Available Tools
3 toolsquery_agent_trustQuery DJZS Agent Trust ScoreAInspect
Query an agent's DJZS trust score, aggregated on-chain (Base mainnet) from its audit history and indexed via the DJZS subgraph. USE BEFORE delegating work, releasing escrow, or executing agent transactions. Returns totalAudits, pass/fail counts, failRate, latest verdict/risk, and DJZS-S01/DJZS-X01 flag counts. HALT if failRate > 0.3 or DJZS-S01/DJZS-X01 fired more than once.
| Name | Required | Description | Default |
|---|---|---|---|
| agentAddress | Yes | Agent wallet address (0x-prefixed) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully details the tool's behavior: aggregates on-chain audit history, returns specific fields (totalAudits, pass/fail counts, failRate, etc.). No side effects are mentioned, but it's a read-only query, so transparency 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 concise (four sentences) and front-loaded with the core purpose, followed by usage and return details. Every sentence adds value with 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?
Given the tool's simplicity (one parameter, no output schema), the description covers purpose, usage context, return fields, and action thresholds. It feels complete and self-contained.
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 sole parameter 'agentAddress' is described in the schema (pattern and description). The description does not add new semantics beyond what the schema provides, yielding a baseline score of 3.
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 queries an agent's DJZS trust score, specifying the aggregation method (on-chain, Base mainnet, DJZS subgraph). The verb 'Query' and resource 'Trust Score' are specific, and the tool is well-distinguished from sibling tools (query_pol_certificates and verify_pm_trade).
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?
Explicit guidance provided: 'USE BEFORE delegating work, releasing escrow, or executing agent transactions.' Also includes a halt condition based on failRate and flag counts, giving clear action criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
query_pol_certificatesQuery DJZS ProofOfLogic CertificatesAInspect
Query immutable ProofOfLogic certificates stored on Irys Datachain by DJZS Protocol. USE THIS TOOL when you need to verify audit history for an agent or project before delegating work, check FAIL verdicts, or retrieve certificates by Irys tx ID. DO NOT use for on-chain trust scores — use query_agent_trust for those.
| Name | Required | Description | Default |
|---|---|---|---|
| tier | No | Filter by tier | |
| limit | No | Number of results | |
| to_ms | No | Window end (epoch ms). Defaults to now + 1h. | |
| from_ms | No | Window start (epoch ms). Default path auto-narrows (14d then 3d) to stay under the mainnet index timeout; pass an explicit value to reach older certificates (used as-is). | |
| verdict | No | Filter by verdict | |
| targetSystem | No | Project name or wallet address |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only mentions immutability and storage backend but does not explain return behavior, performance, rate limits, or any potential side effects. This lack of detail hurts transparency.
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: the first states the purpose, the second provides usage guidance. It is concise, front-loaded, and every sentence serves a clear purpose without extraneous 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?
Given the six parameters and no output schema, the description lacks information about the response format, what certificates contain, or how to interpret verdicts. The agent is left without a clear understanding of what the tool returns, which is critical for a verification 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 100%. The tool description does not add any extra meaning beyond the parameter descriptions already present in the input schema. Therefore, it meets the baseline but adds no additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Query' and the resource 'immutable ProofOfLogic certificates stored on Irys Datachain by DJZS Protocol'. It explicitly distinguishes from sibling tools by advising when to use this tool and when to use query_agent_trust.
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 explicit guidance on when to use this tool (verify audit history, check FAIL verdicts, retrieve by tx ID) and when not to (on-chain trust scores), naming the alternative tool query_agent_trust.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
verify_pm_tradeAInspect
Deterministic pre-execution audit of a prediction-market trade thesis. Extracts the reasoning, audits it against the calibrated DJZS-M taxonomy (M01 narrative/resolution gap, M02 falsification absent, M03 probability unsourced, M04 consensus-as-edge advisory), and returns PASS->PROCEED, FAIL, or WAIT->HALT with flagged defects and a reproducible verdict_hash. Audit before act. Paid tool: 2 USDC per audit via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| intent | Yes | Free-text prediction-market trade thesis to audit | |
| agent_address | No | Optional agent wallet (0x). If set, this audit updates that agent's on-chain DJZS trust score | |
| target_system | No | Optional agent/project identifier; becomes the Target-System tag on the anchored PoL certificate |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only provide a title, so description carries the behavioral burden. It discloses determinism, reproducibility (verdict_hash), and the cost (2 USDC via x402). No contradictions with annotations. Could mention that it is likely read-only, but not required.
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 (3 sentences) and front-loads the purpose. Every sentence adds value: taxonomy, outputs, action prompt, payment detail. 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 no output schema, the description covers the core: outputs (PASS, FAIL, WAIT) and verdict_hash. It explains the taxonomy context. Could specify return format, but it's 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?
Schema coverage is 100%, so baseline is 3. The description adds significant semantics for optional parameters: agent_address updates on-chain trust score, target_system becomes a PoL tag. Required param intent is adequately described in 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 identifies the tool's purpose: a deterministic pre-execution audit of a prediction-market trade thesis, with specific taxonomy and outputs. It distinguishes from sibling tools (query_agent_trust, query_pol_certificates) which are queries, not audits.
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 states 'Audit before act', indicating when to use. It also mentions the tool is paid (2 USDC), which is a key usage consideration. However, it does not explicitly state when not to use or provide alternative tools for similar tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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