Secretaria de Inspeção do Trabalho: CAEPI
Server Details
Secretaria de Inspeção do Trabalho: CAEPI, official-source lookup. Platform-hosted, pay per query wi
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mcp-dir/sit_caepi-mcp
- GitHub Stars
- 0
- Server Listing
- sit_caepi-mcp
Available Tools
7 toolsauthenticateAIdempotentInspect
MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token. Best: add it to this server's config as a header Authorization: Bearer <token> for a permanent, non-expiring connection. Or paste it here for a session-only login: call with { token: "" } after the user pastes, or with no args to get the link.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds meaningful context beyond annotations: explains that calling with no args returns a link, and that token usage is for session login. Annotations already declare idempotentHint=true, readOnlyHint=false, destructiveHint=false; description does not contradict these and adds clarity on how the authentication flow works, including the permanent vs session distinction.
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, each carrying essential information. The description is front-loaded with purpose, then presents the recommended best practice and an alternative. No wasted words; every clause adds value. Well-structured with 'Best:' and 'Or' guiding the agent.
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 tool with one optional parameter, no output schema, and moderate complexity, the description covers purpose, usage modes, and parameter semantics. It implies the output (a link) and explains how to use both modes. It could be more explicit about success/failure responses but is adequate for an authentication 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?
While schema only defines 'token' as an optional string, description explains its semantic role: 'token: "<jwt>"' for session login, and that omitting it yields a link. This adds practical meaning beyond schema, even though schema coverage is 0% because description does not formally document each parameter but does in context.
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?
Clear purpose: authenticates IDE agents, specifically for browser login and token exchange. It's the only authentication tool among siblings, so differentiation is inherent. Verb+resource is specific: 'log in' and 'access token'.
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 two distinct usage modes: permanent config via header, and session-only via token or no-args to get link. Gives explicit call patterns. While it doesn't explicitly state 'use this when... vs alternatives', the context makes it obvious when authentication is needed, and no sibling serves this role.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
connectARead-onlyIdempotentInspect
Returns connection status and URLs. When all providers are connected, returns authenticated:true and empty pending[]. When credentials are missing, returns connect_url for the toolkit and per-install URLs.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, non-destructive. The description adds transparency by explaining the conditional outputs (authenticated true vs. connect_url). No contradictions, and it enhances understanding of behavior.
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 redundant wording. All information is essential and directly relevant to the tool's 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 sufficiently explains return values including authenticated flag, pending array, connect_url, and per-install URLs. Complete for a no-parameter status 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?
No parameters exist, so baseline score of 4 applies. The description does not need to explain parameters, and it does not introduce any ambiguity.
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 that the tool returns connection status and URLs, distinguishing it from sibling tools like 'authenticate' which likely perform authentication actions. The description specifies the resource and 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?
Describes when it returns authenticated status vs. missing credentials, but does not explicitly contrast with alternatives like 'authenticate'. Implicitly clear for status checking, but could be more explicit about when to use this versus other siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
marketplaceAInspect
The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them. Covers capability requests like "find an MCP that does X", "consulta um CPF", "is there a tool for Y". Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile (every tool with its id + params, pricing, auth) so you pick the right tool_id → invoke RUNS that tool. KEY: invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit and without bloating the tool list. If the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link (the user opens it, then you retry). Use install only to make an MCP PERMANENT in the active toolkit (its tools then show up natively in future sessions); prefer invoke for a single/occasional use. list_tools lists what is callable right now. subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits. Search/describe flag installed_in_toolkit vs installed_in_workspace. Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin. It also carries the mcp.ai PROMPT LIBRARY, which is about ready-made prompt TEXT rather than MCPs: search_prompts finds one, get_prompt returns its full text with {{variables}} filled, and publish_prompt saves a prompt and returns a shareable mcp.ai/p/ link that opens without login.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | ||
| action | No | search | |
| mcp_id | No | ||
| message | No | ||
| tool_id | No | ||
| arguments | No | {} | |
| immediate | No | ||
| tier_slug | No | ||
| prompt_body | No | ||
| prompt_slug | No | ||
| prompt_tool | No | ||
| prompt_vars | No | {} | |
| conversation | No | [] | |
| prompt_title | No | ||
| request_name | No | ||
| cancel_reason | No | ||
| cancel_comment | No | ||
| prompt_targets | No | ||
| report_context | No | ||
| prompt_category | No | ||
| request_details | No | ||
| prompt_description | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations, the description discloses key behavioral traits: invoke runs one-off without installing or bloating the toolkit, missing credentials produce a connect link, empty wallet produces a checkout/top-up link with a retry instruction, and writes require workspace owner/admin. This is substantive behavioral context with no contradiction against readOnlyHint=false.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and front-loaded, opening with the core flow and the KEY invoke behavior. It contains almost no wasted wording, but the single long paragraph structure makes it harder to scan; bullets or section breaks would improve navigability for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex 23-parameter, multi-action tool with no output schema, the description covers most major flows: search→describe→invoke, install vs invoke, permissions, billing/subscription, request_mcp, list_tools, and the prompt library. However, it omits the 'resume' action entirely and does not describe return shapes or several parameter semantics, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% for 23 parameters, so the description carries a heavy burden. It explains the meaning of the central action enum and core params like mcp_id, tool_id, and prompt_vars implicitly, but many params (limit, immediate, tier_slug, cancel_reason, cancel_comment, prompt_targets, report_context, request_details, prompt_body, prompt_slug, etc.) remain unexplained.
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 that marketplace is the official mcp.ai catalog/execution layer, covering search, describe, invoke, install, billing, and prompt-library actions. It distinguishes itself from siblings like authenticate/connect/show_version by focusing on MCP discovery and execution rather than auth or system info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit guidance on when to use invoke versus install ('prefer invoke for a single/occasional use'; 'use install only to make an MCP PERMANENT'), when list_tools applies, and when request_mcp is the right call. It does not explicitly address when to use sibling authenticate/connect instead of the marketplace's connect-link flow, which is a minor gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
report_bugAIdempotentInspect
Report a bug, missing feature, or send feedback. Include the conversation array with recent messages for reproduction.
| Name | Required | Description | Default |
|---|---|---|---|
| context | No | ||
| message | Yes | ||
| conversation | No | [] |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate this is a write operation (readOnlyHint=false) and idempotent. The description adds that the conversation should be included for reproduction, but doesn't disclose other behaviors like outcome or auth. With annotations covering safety profile, a 3 is appropriate.
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, directly states purpose and usage, 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?
Simple tool with good annotations; description covers what it does and how to use it. Missing details about outcome but acceptable given simplicity.
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% property descriptions, so description must compensate. It explains conversation (include recent messages) but leaves message and context implicit. Partial 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 tool reports a bug, missing feature, or feedback, with a specific verb and resource. It distinguishes itself from siblings (auth, version, etc.) by its explicit 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?
It implies when to use (when reporting issues) and instructs to include conversation for reproduction. However, it doesn't explicitly state when not to use or mention alternatives, though siblings are clearly unrelated, so context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
show_versionARead-onlyIdempotentInspect
Show the current MCP platform and adapter versions.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, non-mutating operation. The description adds no extra behavioral context beyond that, but it doesn't contradict the annotations. With annotations covering the safety profile, a 3 is appropriate.
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 with no wasted words. It is front-loaded with the action and resource. Perfectly concise for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema, clear purpose), the description is complete. It doesn't need to explain return values because there is no output schema, but the purpose is clear. The annotations provide safety context, so the description is 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?
The tool has zero parameters, and the schema description coverage is 100% (vacuously). The description doesn't need to explain parameters since there are none. The baseline for 0 params is 4, and the description is sufficient.
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: showing current MCP platform and adapter versions. It uses a specific verb ('show') and resource ('versions'), and while it doesn't explicitly distinguish from siblings, the sibling tools have different purposes (authentication, connection, marketplace, etc.), so it is clear 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?
The description implies usage: when you need to know the current versions. It doesn't explicitly state when not to use it or mention alternatives, but given the simplicity and the sibling tools' distinct purposes, the context is clear. No exclusions are needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sit_caepi_consultarCRead-onlyIdempotentInspect
Secretaria de Inspeção do Trabalho: CAEPI, consulta em fonte oficial. Hospedado pela plataforma, sem credenciais da plataforma, pague por consulta com crédito pré-pago. Consulta informação de fontes e órgãos oficiais brasileiros (a mesma disponível ao cidadão), não é dado sigiloso. O cliente é o controlador dos dados e responde pela finalidade legítima (LGPD).
| Name | Required | Description | Default |
|---|---|---|---|
| ca | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only and idempotent. The description adds valuable context: payment model (prepaid consultation), no platform credentials needed, data is non-confidential, and client is LGPD data controller. Contradicts no annotation. It doesn't cover error handling or rate limits, but what's added is meaningful.
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 ~4 sentences, covering purpose, hosting, payment, and legal responsibility. It's somewhat verbose but relevant. The key purpose is stated first, but the legal and payment details could be shortened. Not overly long, but not tight.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite low complexity (1 param, no output schema), the description fails to explain the required 'ca' parameter, the format of data returned, or any usage constraints like rate limits. With low schema coverage (0%), the description needed to fill that gap and didn't.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 1 required parameter 'ca' with zero description coveragecars. The tool description does not explain what 'ca' represents, its format, or expected values. Without that, the agent cannot correctly provide input.
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 indicates a consultation of CAEPI via official Brazilian sources, using the verb 'consultar' (consult) and a specific resource name. It distinguishes from siblings which are generic toolkit utilities, though it could be more explicit about what data is returned.
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 or not use this tool. The description provides context (official source, pay-per-use, not secret data) but does not mention alternatives or exclusions. Sibling tools are unrelated, so it's implied but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
toolkit_infoARead-onlyIdempotentInspect
Returns the current toolkit state: installed MCPs, their connection status, the accounts connected to each one, and how many catalog tools each exposes.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description adds specific details about what the tool returns (installed MCPs, connection status, accounts, catalog tool counts), going beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, clear and concise, front-loaded with the verb 'Returns'.
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 zero-parameter, no-output-schema tool, the description fully covers what it returns and serves its purpose. No missing information.
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?
No parameters exist, so there are no semantic gaps. The description effectively explains the tool's output without needing parameter details.
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 ('Returns') and identifies the resource ('current toolkit state') with detailed components: installed MCPs, connection status, accounts, and catalog tools. This clearly distinguishes it from sibling tools that focus on actions like authentication, version, and bug reporting.
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 toolkit state but does not explicitly state when to use it or provide alternatives. Given the read-only nature and clear purpose, context is implied but no formal guidelines are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
No tool schema history has been recorded yet.
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
The tools separate into distinct purposes: authenticate is for login/token acquisition, connect is for connection status, marketplace is for discovering and running MCPs, sit_caepi_consultar is for official Brazilian labor-source queries, while toolkit_info, report_bug, and show_version are general-purpose status/maintenance tools. Some overlap exists between authenticate/connect and marketplace/toolkit_info, but the descriptions delineate their boundaries sufficiently.
Tool names follow inconsistent conventions: five use camelCase (authenticate, connect, marketplace) while four use snake_case (sit_caepi_consultar, toolkit_info, report_bug, show_version). There is also no consistent verb-object structure: 'sit_caepi_consultar' mixes a domain prefix with a verb, and 'toolkit_info' uses a noun rather than a verb. No discernible pattern by which an agent could predict tool names.
Seven tools is a reasonable size for a server that combines authentication, an MCP catalog, a domain-specific query worker, and status/feedback functions. It is neither an extreme single-domain emptiness nor a bloated them need to be expanded, and each tool can be justified as part of the larger portal/toolkit vision.
The main gap is domain-specific coverage: for a 'CAEPI' server there is only one tool dedicated to official labor-question queries (sit_caepi_consultar), which may work but does not cover ongoing processes beyond, say, obtaining records/sharing workers or other closed processes. On the platform side, the marketplace and data are useful but the platform is more of a meta-platform than a complete official labor inspection itself.