byte-protocol
Server Details
Per-byte USDC data feeds + oracles for AI agents on Arbitrum. Verifiable, no token, no API keys.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- 0rkz/byte-mcp-server
- GitHub Stars
- 0
- Server Listing
- BYTE Protocol
Glama MCP Gateway
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Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4/5 across 14 of 14 tools scored. Lowest: 3.4/5.
Each tool targets a distinct action: buying single data, subscribing, publishing, registering, checking status, querying oracle, etc. Even similar tools like byte_list_feeds and byte_search_publishers are clearly separated by object (feeds vs publishers).
All tool names follow the consistent pattern 'byte_verb_noun' (e.g., byte_buy_data, byte_subscribe, byte_publish_data). Underscores separate words, and the verb is always action-oriented.
14 tools cover the protocol's lifecycle for both consumers and publishers without being excessive. Each tool serves a clear purpose, and the count is well within the 3-15 sweet spot.
Core operations (subscribe, publish, register, buy, query orchestrated) are covered. Minor gaps like unregistering as publisher or viewing subscription payment history are absent but not critical for typical use.
Available Tools
14 toolsbyte_buy_dataAInspect
Buy a single data packet from any BYTE Library feed via the x402 payment gateway. No subscription, no allowance, no prior on-chain setup — pay-per-call USDC settlement. The MCP server signs an EIP-3009 transferWithAuthorization on behalf of the wallet whose PRIVATE_KEY is configured, the x402 facilitator submits the tx, and the data comes back inline with the on-chain settlement tx hash. Use byte_subscribe instead if you want a continuous stream of broadcasts from a publisher. The catalog of available feed slugs lives at https://x402.payperbyte.io/feeds (free GET). Requires PRIVATE_KEY env var on the MCP server and USDC balance on the configured wallet (Arbitrum Sepolia).
| Name | Required | Description | Default |
|---|---|---|---|
| feed | Yes | Feed slug — one of: weather, earthquakes, space-weather, news-feed, code-pulse, runtime-eol, threat-intel, btc-metrics, pkg-facts, cve-facts, wiki-facts, merchant-trust, crypto-top100, defi-yields, byte-status. (For fact-oracle Q&A use byte_query_fact instead — it uses a different request-response flow.) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description discloses the payment flow: MCP server signs an EIP-3009 transfer, facilitator submits tx, data returns inline with tx hash. It mentions no prior setup needed, but lacks details on failure modes 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 a single paragraph of about 100 words, dense but clear. Every sentence adds value, though could benefit from slight structuring (e.g., bullet points) for quick scanning.
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 purpose, usage, prerequisites, and alternatives. However, lacking details on output format (vague 'inline with tx hash') and error scenarios. No output schema means description should compensate more.
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 does not add significant parameter-level information beyond what the schema provides; it only repeats 'feed slug' and references the catalog URL. Minor value from mentioning byte_query_fact alternate.
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: buying a single data packet via x402 payment gateway. It differentiates from sibling tool byte_subscribe for continuous streams, and the input schema reinforces the single parameter 'feed' with a list of allowed slugs.
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 when to use this tool (pay-per-call, no subscription) and when to use byte_subscribe instead. Prerequisites (PRIVATE_KEY env var, USDC balance on Arbitrum Sepolia) are mentioned. However, it does not explicitly state exclusions or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_check_subscriptionAInspect
Check if an address is subscribed to a specific publisher on BYTE Library.
| Name | Required | Description | Default |
|---|---|---|---|
| publisher | Yes | Publisher Ethereum address (0x...) | |
| subscriber | Yes | Subscriber Ethereum address (0x...) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states 'Check if an address is subscribed', failing to disclose return format, side effects (likely none), or any other behavioral traits. The description carries the full burden but adds little beyond the obvious.
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?
Single, concise sentence that is front-loaded with the action and resource. No extraneous 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?
For a simple boolean check, the description is fairly complete. It clearly states the purpose and required inputs. No output schema exists but the return value is inferrable. Minor gap: no mention of edge cases or the specific return type.
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 clear descriptions for each parameter. The tool description does not add additional meaning beyond what the schema already provides, 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 uses a specific verb ('Check') and resource ('if an address is subscribed to a specific publisher'), clearly distinguishing it from sibling tools like byte_subscribe or byte_unsubscribe.
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., byte_subscription_health). The usage is implied but lacks when-not-to-use or context preferences.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_get_network_statsAInspect
Get BYTE Library network-wide statistics: total publishers, messages streamed, and total subscriber fees settled in USDC.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It discloses the return values but lacks details on behavioral traits such as cost, rate limits, or side effects. The tool appears to be a simple read-only operation, but this is not explicitly stated.
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 that is concise and front-loaded with the action and resource. Every word adds value, 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?
Given the simplicity (no parameters, no output schema), the description is sufficiently complete by listing the three statistics returned. It could specify format or precision, but overall 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?
There are zero parameters, so the baseline is 4. The description adds no parameter information because none exist. Schema coverage is 100% (no parameters), so no gaps.
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 'Get' and the resource 'BYTE Library network-wide statistics', listing specific statistics (total publishers, messages, subscriber fees). It distinguishes itself from siblings, none of which offer network-wide stats.
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 tool is for obtaining broad network overview, and with no parameters, usage is straightforward. However, it does not explicitly mention when to use it versus alternatives or provide any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_get_publisherAInspect
Get on-chain info for a specific BYTE Library publisher: status, subscriber and message counts, USDC revenue, and the registered schema (size bounds, cadence, price-per-KB).
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Publisher Ethereum address (0x...) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It indicates a read operation ("Get on-chain info") but lacks details on potential side effects, authorization requirements, or error behavior. The description is basic but not misleading.
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 sentence that efficiently lists the returned information. It is front-loaded with the purpose, and there is no wasted text. Slightly longer due to enumerating fields, but still concise.
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 explains what data is returned (status, counts, revenue, schema details) given no output schema. However, it does not mention what happens if the address is invalid or if the publisher does not exist, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description of the address parameter. The tool description adds no additional meaning to the parameter beyond what the schema already provides, so it meets the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves on-chain info for a specific BYTE Library publisher, listing specific data fields (status, counts, revenue, schema). This distinguishes it from siblings like byte_search_publishers which likely search/filter.
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 use for getting details of a known publisher by address but does not explicitly state when to use it versus alternatives like byte_search_publishers or byte_register_publisher. No exclusions or alternative guidance provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_get_token_balancesAInspect
Get USDC and ETH balances for an address on Arbitrum Sepolia. USDC is the BYTE Library settlement asset; ETH covers gas.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Ethereum address (0x...) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It clearly states the tool gets balances, implying a read-only operation. However, it does not disclose any potential side effects, authentication requirements, or rate limits, but for a simple get operation, the 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 two sentences (20 words) with no redundancy. Every word is necessary, and it is front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description could explain return values but does not. However, for a simple balance check, the network and assets are specified, making it reasonably complete for an AI agent to infer expected output.
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 the 'address' parameter described as 'Ethereum address (0x...)'. The description adds overall context (USDC and ETH, Arbitrum Sepolia) but does not add meaning specific to the parameter beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it gets USDC and ETH balances for an address on Arbitrum Sepolia, providing a specific verb, resource, and scope. It clearly distinguishes from sibling tools like byte_buy_data or byte_subscribe by focusing on balance retrieval.
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 checking settlement and gas balances but lacks explicit guidance on when to use this tool vs. alternatives. No when-not-to-use or alternative tool names are provided, so the guidance is minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_list_feedsBInspect
List all active data feeds in the BYTE Library catalog with topics, price-per-KB, and frequency.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description lacks behavioral details such as pagination, rate limits, authentication requirements, or the meaning of 'active.' It only states a simple list operation, which is minimal for full 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 a single, direct sentence with no unnecessary words. It efficiently conveys the tool's purpose and output.
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, parameterless list tool, the description is mostly complete. It specifies what is listed and the returned fields. However, it omits details like error handling or data freshness, which are minor 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?
The input schema has no parameters, and schema description coverage is 100%. The description adds context about the output but does not clarify any parameter semantics beyond what the schema already conveys. Baseline of 3 is appropriate here.
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 active data feeds in the BYTE Library catalog, specifying the returned information (topics, price-per-KB, frequency). This distinguishes it from sibling tools like byte_buy_data or byte_subscribe, which handle transactions and subscriptions.
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 compared to alternatives. There are no prerequisites, exclusions, or hints about appropriate contexts, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_list_my_subscriptionsAInspect
List every active subscription for a given wallet address. Each entry has the publisher address, topic, status, when you subscribed, messages received in 7/30 days, USDC spent in 7/30 days, and the timestamp of the last message received. Use this to see what you're currently paying for and decide whether to unsubscribe.
| Name | Required | Description | Default |
|---|---|---|---|
| indexerUrl | No | Optional indexer URL override (default: BYTE_INDEXER_URL env or http://localhost:8080) | |
| subscriber | Yes | Wallet address to list subscriptions for |
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. It discloses that it lists only active subscriptions and specifies the fields in each entry (publisher, topic, status, etc.). This gives good behavioral context for a read operation, though it could mention if historical subscriptions are excluded.
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 with no wasted words. First sentence states action and output fields; second provides usage guidance.
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 and the description covers action, output fields, and usage context. No output schema exists, but the description lists key fields. Potential missing info: pagination or ordering, but not critical for a listing 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% with both parameters well-described. The description does not add new semantic detail beyond the schema, 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 clearly states the verb 'List', resource 'subscriptions', and scope 'active for a given wallet address'. It distinguishes well from siblings like byte_check_subscription and byte_subscription_health.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this to see what you're currently paying for and decide whether to unsubscribe', providing clear context for when to use. It does not explicitly state alternatives but is adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_publish_dataAInspect
Publish data to a subscriber via the BYTE Library DataStream contract. Hashes the payload, records size on-chain, and settles the fee in USDC. Requires PRIVATE_KEY.
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | Data payload to publish (will be hashed on-chain) | |
| maxFee | Yes | Maximum fee in USDC willing to pay for this publish (e.g. 0.05) | |
| subscriber | Yes | Subscriber Ethereum address (0x...) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses that it hashes the payload, records size on-chain, settles USDC fee, and requires PRIVATE_KEY. However, it does not mention error states, gas costs, reversibility, or what happens on failure, leaving some behavioral traits unspecified.
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 long, front-loaded with the core purpose, and every sentence adds value. No redundant or extraneous information.
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 of an on-chain interaction tool, the description covers the main actions but omits potential prerequisites (e.g., subscriber must be subscribed), return values, and error handling. It is adequate but 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?
The input schema has 100% coverage with descriptions for all parameters. The tool description adds context about the overall process (e.g., 'Hashes the payload, records size on-chain, and settles the fee in USDC') but does not significantly enhance understanding of individual parameters beyond the schema. 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 clearly states the action (publish), target (subscriber via BYTE Library DataStream contract), and details what happens (hashes payload, records size, settles fee). It distinguishes this from sibling tools like byte_buy_data and byte_subscribe by focusing on publishing data to an existing subscriber.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for publishing data to a subscriber, but does not explicitly state when not to use it or mention alternatives. However, the context of sibling tools provides implicit guidance, and the purpose is clear enough for an agent to infer appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_query_factAInspect
Query a BYTE Library fact-oracle publisher for a verified factual answer with citations. Posts the question to a registered fact-oracle publisher (topic='fact-oracle'), waits for the on-chain BroadcastStreamed response, and returns the answer plus structured citation URLs. Use for grounding LLM outputs in real-time verified information.
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | The factual question to ask (e.g. 'What was last night's Lakers vs Warriors score?'). Should be specific and verifiable. | |
| topic_filter | No | Optional topic filter (e.g. 'fact-oracle' default; future: 'sports', 'finance'). | |
| max_byte_cost | No | Max response payload bytes you're willing to pay for (defaults to 2000, ≈$1 at $0.0005/byte). Publisher refuses if can't fit answer. | |
| min_publisher_pqs | No | Minimum PQS to consider (BPS scale, 0-10000). 9000 = Elite-only, 7500 = Premium+. | |
| subscriber_address | Yes | Your wallet address. You MUST be subscribed to the chosen publisher (with sufficient USDC escrow) or the publisher's on-chain broadcast will be skipped. | |
| max_response_latency_ms | No | Max time to wait for the publisher's broadcast (default 30000 ms). Local-LLM publishers (Ollama + Searxng + 3-sample NLI gate) take ~30-60s; Anthropic + passthrough takes ~10-20s. Hard ceiling 180s. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description partially covers behavior (posting question, waiting for broadcast, returning answer/citations) but omits details on subscription prerequisites, cost implications, and failure modes.
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: one stating purpose, the other explaining process and usage. No redundant information.
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 6 parameters and no output schema, the description covers the tool's purpose, process, and use case adequately. Missing minor details on expected output structure, but mentions citations.
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 3. The description adds context about the tool flow but does not significantly enhance parameter 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 it queries a 'fact-oracle publisher for a verified factual answer with citations.' It uses specific verbs and resources, and differentiates from sibling tools like byte_publish_data or byte_get_publisher.
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 suggests using for 'grounding LLM outputs in real-time verified information' but does not explicitly state when not to use or provide direct alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_register_publisherAInspect
Register as a data publisher on BYTE Library. Registers a schema and the publisher on-chain. Requires PRIVATE_KEY. BYTE Library v1 publishers are first-party and unstaked — leave stake at '0'; a non-zero USDC stake is approved to DataRegistry first if you choose to post one.
| Name | Required | Description | Default |
|---|---|---|---|
| stake | Yes | USDC reputation stake to post, as a decimal string. Default '0' — BYTE Library v1 publishers are unstaked. | |
| topic | Yes | Data feed topic (e.g. 'eth-price', 'weather-nyc', 'gas-tracker') | |
| maxSize | Yes | Maximum payload size in bytes per message | |
| frequency | Yes | Expected publishing frequency in seconds | |
| pricePerKB | Yes | Price per kilobyte in USDC (e.g. 0.003) | |
| expectedSize | Yes | Expected payload size in bytes per message |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It reveals the on-chain nature and the stake approval process for non-zero stakes. However, it fails to mention side effects like gas costs, potential failure conditions (e.g., already registered), or post-registration behavior. This is adequate but not thorough.
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 that are short and to the point. The first sentence delivers the core purpose, and the second adds essential usage guidance. 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?
For a registration tool with 6 parameters and no output schema, the description explains the on-chain action and stake handling but lacks information on return values, error conditions, or post-registration steps. This is minimally 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 100% with descriptions for all 6 parameters. The description adds value by contextualizing the default stake, explaining the first-party unstaked model, and providing examples for topic. This goes beyond the baseline 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?
Clearly states the verb 'register' and resource 'data publisher', and specifies on-chain registration. It uniquely describes the tool's function among siblings, which include no other registration tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Mentions the requirement of PRIVATE_KEY and provides guidance on stake usage: default '0' for unstaked publishers, and notes that non-zero stakes require prior approval. However, it does not explicitly state when not to use this tool or describe prerequisites beyond the key.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_search_publishersAInspect
Search BYTE Library publishers by topic and sort order. Returns publisher addresses, topics, subscriber counts, message counts, and price-per-KB.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results to return (default 20) | |
| query | No | Topic keyword to search (e.g. 'weather', 'crypto', 'cve') | |
| sortBy | No | Sort field: 'subscribers', 'revenue', 'messages' |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must carry the burden of behavioral disclosure. It indicates a read operation by mentioning search and returns, but lacks details on side effects, rate limits, or authentication requirements. This is adequate but not comprehensive.
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 that front-load the purpose and return value. 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 no output schema or annotations, the description adequately covers the purpose and return fields. However, it lacks usage context, behavioral details, and edge cases, which would be helpful for a tool with three parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema coverage is 100%, meaning each parameter has a description. The tool description adds no additional meaning beyond the schema's 'Topic keyword' for query and 'Sort field' for sortBy. 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 clearly states the action 'Search', the resource 'BYTE Library publishers', and the criteria 'by topic and sort order'. It also lists the return fields, distinguishing it from siblings like byte_get_publisher which likely retrieves a single publisher.
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. While the sibling list provides context, the description does not specify scenarios, prerequisites, or exclusions, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_subscribeAInspect
Subscribe to a BYTE Library publisher's data feed. By default also sets USDC allowance to DataStreamLib to type(uint256).max so the subscription doesn't silently lose payments when allowance depletes (the contract's allowance-skip path emits DataStreamed with amount=0 on transferFrom failure rather than reverting). Pass skipAllowance: true to opt out and set a finite cap manually. Requires PRIVATE_KEY.
| Name | Required | Description | Default |
|---|---|---|---|
| publisher | Yes | Publisher Ethereum address (0x...) to subscribe to | |
| skipAllowance | No | If true, don't bundle the USDC approve(max) call. Default false. Auto-approve is also skipped when the wallet already has ≥ $1000 USDC of allowance to DataStreamLib. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description fully shoulders the behavioral transparency burden. It details the default allowance setting, the contract's failure path, the auto-approve skip condition, and the PRIVATE_KEY requirement, giving comprehensive insight into side effects and prerequisites.
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 tightly written: it opens with the core purpose, then efficiently communicates default behavior, opt-out mechanism, and prerequisite. Every sentence earns its place 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?
The description covers input semantics, side effects, and prerequisites adequately for a subscribe action. Given no output schema, it does not describe return values, which is a minor gap, but the tool's behavior is well-explained.
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%, providing parameter descriptions. The description adds value by explaining the default behavior of skipAllowance and the condition for auto-approve skipping, which goes beyond the schema's basic boolean meaning.
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 'Subscribe to a BYTE Library publisher's data feed.' It is specific about the verb (subscribe) and resource (publisher's data feed), and distinguishes from siblings like byte_buy_data or byte_check_subscription by focusing on the subscription 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 explains when to use skipAllowance (opt out of auto-approve) and mentions the PRIVATE_KEY requirement. However, it does not explicitly compare with alternatives or state when not to use this tool, which would improve guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_subscription_healthAInspect
Get the content-drift signal for a publisher. Compares their last 7 days of publishing activity (cadence, message count) against their 23-day baseline (days 8-30). Returns 'stable' (steady publishing), 'moderate' (20-50% cadence shift or 24-48h silence), 'significant' (>50% shift or >48h silence), or 'unknown' (new publisher, insufficient baseline). Use this to detect when a publisher you subscribe to has pivoted content or gone dormant.
| Name | Required | Description | Default |
|---|---|---|---|
| publisher | Yes | Publisher address to check | |
| indexerUrl | No | Optional indexer URL override |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses behavioral details: the algorithm (7 days vs 23-day baseline), threshold meanings (20-50% shift, 24-48h silence), and handling of new publishers ('unknown'). No contradictions.
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: first states the tool's purpose and logic, second provides usage guidance. Every sentence adds value, 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?
Although there is no output schema, the description explicitly lists possible return values ('stable', 'moderate', 'significant', 'unknown') and their conditions, effectively compensating. For a tool of this complexity, the description is sufficiently 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 100%, both parameters are already described in the input schema. The description adds no additional semantics beyond what is in the schema, so baseline score 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 'Get the content-drift signal for a publisher' and explains the comparison logic and return values. This distinguishes it from sibling tools like byte_check_subscription or byte_get_publisher, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes an explicit usage recommendation: 'Use this to detect when a publisher you subscribe to has pivoted content or gone dormant.' While it doesn't mention when not to use it or list alternatives, the context is clear enough for appropriate selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
byte_unsubscribeAInspect
Unsubscribe from a publisher's data feed. Takes effect next block: no more billing, no more data flow. Reversible — you can resubscribe later via byte_subscribe. Use this when a publisher has pivoted content (check with byte_subscription_health first) or when you simply don't want the feed anymore. Requires PRIVATE_KEY for the connected wallet.
| Name | Required | Description | Default |
|---|---|---|---|
| publisher | Yes | Publisher address to unsubscribe from |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that effect takes place 'next block', states it is reversible, and requires PRIVATE_KEY. No annotations provided, so description carries full burden and meets it well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences: first states the action, second explains effect and reversibility, third gives usage contexts and requirement. No wasted words, well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description covers purpose, effect, reversibility, when to use, and a key requirement. 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?
Schema description coverage is 100% with a clear description for the only parameter. The tool description does not add new information about the parameter beyond what schema already provides.
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 the action 'Unsubscribe from a publisher's data feed' and explains the effect ('no more billing, no more data flow'). Distinguishes from siblings like byte_subscribe and byte_subscription_health by mentioning them explicitly.
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 explicit when-to-use: 'when a publisher has pivoted content' or 'when you simply don't want the feed anymore'. Mentions checking byte_subscription_health first. No explicit when-not-to-use, but adequate for a simple tool.
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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{
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