Search 10k+ live cybersecurity jobs from 246 security companies, plus salary benchmarks and stats.
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Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 3.8/5 across 5 of 5 tools scored.
Each tool has a clearly distinct purpose: get_job for a single job, market_stats for aggregate stats, salary_benchmark for salary data, search_jobs for searching, and top_employers for company rankings. No overlap.
All tool names follow a consistent lowercase_with_underscores pattern (e.g., get_job, market_stats, salary_benchmark, search_jobs, top_employers). No mixing of conventions.
5 tools is well-scoped for a job board server: covers retrieval, search, statistics, benchmarks, and employer rankings without unnecessary bloat.
The tool set covers core job board functionality (search, detail, stats, salary info, top employers). Minor gap: no explicit list_all tool, but search_jobs with broad criteria and a full-list URL effectively covers that.
get_jobAInspectGet one job by id: role details, a short description excerpt, and the canonical job-page URL (which is also where to apply).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Job id from search_jobs results |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions the tool returns specific data, but it does not disclose whether the operation is read-only, requires authentication, or has any side effects. This is adequate but minimal.
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 conveys the tool's purpose and output. No redundant information, and it is front-loaded with the key action.
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 get-by-id tool with one parameter and no output schema, the description adequately explains what the tool does and what it returns. It mentions three components of the response, which is sufficient for an agent to understand the basic behavior.
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%, so the baseline is 3. The description does not add new parameter semantics beyond the schema's 'Job id from search_jobs results'. No additional details about format or constraints are provided.
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 one job by id' and specifies the returned data: role details, description excerpt, and apply URL. It distinguishes from sibling 'search_jobs' which lists multiple jobs, making the purpose unambiguous.
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 id comes from 'search_jobs results' (via the parameter description), guiding the agent to use search_jobs first. However, it does not explicitly state when to use this tool over others or list any prerequisites beyond having the id.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
market_statsAInspectLive aggregate cybersecurity hiring stats: total open security roles, new this week, remote share, salary-disclosure rate, and top specializations / seniorities / countries.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description mentions 'live' but doesn't disclose data freshness, rate limits, or side effects. For a simple read-only tool, it's adequate but not rich.
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 listing all relevant stats upfront. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, description covers the main purpose well. Could mention output format or pagination, but tool is simple.
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; baseline is 4. Schema description coverage is 100% (trivially). Description adds no parameter info, but none needed.
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?
Description clearly states it provides live aggregate cybersecurity hiring stats with specific metrics listed. Distinguishes from siblings like get_job (single job) and search_jobs (search).
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 vs alternatives. The description implies it's for aggregate stats, but lacks direct comparison or when-not-to-use advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
salary_benchmarkBInspectCurated cybersecurity salary benchmark bands (USD + local currency) across 21 countries including the US, EU, Gulf (tax-free), India, LatAm, and Africa.
| Name | Required | Description | Default |
|---|---|---|---|
| role | Yes | Role to benchmark | |
| country | No | Optional country name; omit for all 21 countries |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should disclose safety traits (e.g., read-only, any authorization needs) and limitations (e.g., data freshness, defaults when country omitted). It only mentions geographic scope, lacking behavioral context.
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 efficient sentence that front-loads the core purpose and geographic scope. No unnecessary words, though it could be slightly expanded with usage hints without losing conciseness.
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?
No output schema is provided, so the description should explain what the tool returns (e.g., salary ranges, percentiles, currency bands). It only names what the tool covers, not what the output looks like or how to interpret results, leaving the agent underinformed.
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% (both parameters described). The description adds context for the 'country' parameter by listing examples (US, EU, Gulf, India, LatAm, Africa), but adds no additional meaning for the 'role' parameter beyond its enum. 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 tool provides cybersecurity salary benchmark bands across 21 countries, using specific verbs like 'curated' and 'benchmark'. It distinguishes from siblings (e.g., market_stats, search_jobs) by focusing on salary bands.
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 implicitly suggests it's for salary benchmarks across countries, but does not explicitly state when to use it versus alternatives like market_stats or get_job, nor does it mention any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_jobsAInspectSearch live cybersecurity jobs from 200+ security companies (updated hourly). Returns up to 10 matching roles plus the total match count and a browse URL for the full list. All Apply flows go through the returned job URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 5, hard cap 10) | |
| query | No | Free-text search over title / company / location | |
| remote | No | Only remote roles | |
| country | No | Country name, e.g. "Germany" or "United States" | |
| seniority | No | Seniority bucket | |
| specialization | No | Cybersecurity specialization |
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 update frequency ('updated hourly'), result limit ('up to 10'), and output details (total match count, browse URL). It also clarifies that all apply flows go through the returned job URLs. This is sufficient behavioral context.
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 concise sentences, each purposeful. First sentence states the core action, second summarizes output, third clarifies the apply flow. No redundant or irrelevant 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 no output schema, the description covers the key output elements (matching roles, total count, browse URL). It also includes update frequency and scope. It does not cover error handling or empty results, but for a search tool this 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?
Schema description coverage is 100%, so baseline is 3. The description does not add new meaning beyond what the schema provides for any parameter. For example, the 'query' parameter description in the schema already states 'Free-text search over title/company/location'.
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 'Search' and a well-scoped resource 'live cybersecurity jobs from 200+ security companies'. It clearly distinguishes this tool from siblings like 'get_job' (single job) and analytical tools like 'market_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 clearly states what the tool does and mentions it returns a browse URL for full results. However, it does not explicitly state when to use this tool versus alternatives, though the sibling context makes it somewhat clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
top_employersAInspectThe security companies with the most open cybersecurity roles right now (objective open-roles ranking with remote share and pay-transparency rate).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 5, hard cap 10) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It mentions 'objective open-roles ranking with remote share and pay-transparency rate' but does not disclose traits like data freshness, ordering, or any limitations.
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 with all key information front-loaded. No filler 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 simple tool with one optional parameter and no output schema, description adequately specifies what the tool returns. Could include more detail on field names or format, but sufficient for understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'limit', which is well-described in the schema. The tool description adds no extra semantic beyond what the 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?
Description clearly states the tool lists security companies with the most open cybersecurity roles, providing a ranking with remote share and pay-transparency rate. It distinguishes from siblings like get_job (individual jobs) and market_stats (general market 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?
No explicit when-to-use or when-not-to-use guidance, nor alternatives compared to siblings. The context of 'objective open-roles ranking' implies usage for rankings, but no clear exclusion criteria.
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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