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Check Headers

check_headers
Read-onlyIdempotent

Validate HTTP security headers you provide (JSON): CSP, HSTS, X-Frame-Options, X-Content-Type-Options, Permissions-Policy, Referrer-Policy against best practices. Use to test header config before deployment or validate non-public servers; use scan_headers to fetch live. Free: 30/hr, Pro: 500/hr. By default header values are truncated to 500 chars; pass include='full' for the full raw value. Returns {total, by_severity, findings}. No external requests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
headersYesJSON string of HTTP header name-value pairs to validate. Example: '{"Strict-Transport-Security": "max-age=31536000", "X-Frame-Options": "DENY"}'. Include only security-relevant headers you want to analyze.
includeNoDetail level. Default ('') returns slim findings — raw header values capped at 500 chars with total_value_length carrying the honest pre-truncation length. Pass 'full' to restore the full raw value. Allowed: '' or 'full'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds significant behavioral context beyond the annotations: it discloses that no external requests are made, describes the default truncation of header values to 500 chars, explains the include='full' option, and specifies the return shape ({total, by_severity, findings}). Annotations already indicate read-only and idempotent, but the description enriches the behavioral profile substantially.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured: purpose, use cases, rate limit, truncation behavior, return format, and privacy note are all conveyed in just a few sentences. Every sentence contributes unique information without redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter tool with an output schema, the description is highly complete. It covers when to use, alternatives, behavioral details (truncation, no external requests), rate limits, and return format. The existence of an output schema means it need not explain return values in depth. The description leaves no major gaps for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with detailed parameter descriptions, so the baseline is 3. The description adds value by enumerating the specific security headers to validate (CSP, HSTS, etc.), which helps the agent construct meaningful input. It also reinforces the include parameter's truncation behavior, though this is already in the schema. Overall, a modest addition over schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool validates user-provided HTTP security headers against best practices, listing specific header types (CSP, HSTS, X-Frame-Options, etc.). It also distinguishes from the sibling tool by directing users to scan_headers for live fetching, so there is no ambiguity about what this tool does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit usage guidance is provided: 'Use to test header config before deployment or validate non-public servers; use scan_headers to fetch live.' This tells the agent exactly when to choose this tool over the alternative, and also includes rate limit information ('Free: 30/hr, Pro: 500/hr') that affects usage decisions.

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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TDQS

A4.5/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with differences between lookup/search/scan/audit for each domain. However, some overlap exists (e.g., email_mx vs email_security_posture, scan_headers vs contrast_scan) which could cause occasional confusion. Overall, boundaries are well-defined.

Naming Consistency5/5

Tool names follow a consistent verb_noun pattern (e.g., cve_lookup, check_headers, bulk_cve_lookup) with all lowercase underscores. Variations like kev_detail or ssl_check are minor and still predictable. No chaotic mixing of conventions.

Tool Count4/5

54 tools is high but justified by the broad cybersecurity scope (CVE, ATLAS, D3FEND, Sigma, domain, email, IOC, scanning). Some redundancy exists (e.g., three email-related tools), but the count is not excessive given the API's comprehensive feature set.

Completeness5/5

The tool set thoroughly covers the threat intelligence and domain investigation lifecycle: CVE/KEV/exploit/CWE, ATLAS/D3FEND/Sigma, DNS/WHOIS/SSL/subdomains, email security, IOC enrichment, and active scanning. No significant gaps are apparent for the stated cybersecurity purpose.