Bowmark
Server Details
Pre-computed navigation recipes for public websites — skip explore-and-discover.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.8/5 across 2 of 2 tools scored.
The two tools serve entirely different and complementary purposes: 'ask' is for retrieving navigation recipes, while 'report_outcome' is for reporting execution results. There is no overlap in functionality.
Both tool names are imperative verbs, but 'ask' is a single word while 'report_outcome' follows a verb_noun pattern. This minor inconsistency doesn't hinder understanding.
With only two tools, the server is minimal but focused on a specific coordination task. The count is borderline low, but the descriptions cover the core workflow of fetching and reporting recipes.
The tools cover the intended lifecycle: requesting a recipe and reporting its outcome. There are no obvious gaps within the server's defined scope, as actual navigation steps are assumed to be performed by other tools.
Available Tools
2 toolsaskFind a navigation recipe for a website taskAInspect
Pre-computed navigation recipes for public websites. CALL BEFORE any browser action on the open web (navigate, click, fetch, fill, URL guess) — replaces explore-and-discover. Returns { status, id?, fastest_path?, ui_procedure?, verify_more?, error? }.
status=ok: execute exactly. fastest_path first if present (URL-encode {name} into template), else ui_procedure.steps in order. Don't screenshot; read DOM only for the element a step names. If verify_more: true, do one cheap sanity check (page title plausible?) before committing. If step.irreversible, confirm with user. After, call report_outcome once with the returned id.
status=site_not_supported | no_useful_data | synth_invalid: miss, no id. Browse manually.
status=ambiguous_scope: retry with scopeHint set to one of error.scope_options[].pattern.
Skip for: localhost / 127.0.0.1 / *.local / RFC1918 (10., 192.168., 172.16-31.); open-ended search with no destination. On 503 embedder_unavailable/synth_unavailable, retry once after Retry-After.
| Name | Required | Description | Default |
|---|---|---|---|
| site | Yes | Registrable domain, optionally followed by a product-surface path — 'google.com', 'docs.stripe.com', 'google.com/maps'. No scheme/port. A path is treated as an implicit scopeHint when it matches a known surface, so you can skip the ambiguous_scope round-trip for sites with multiple surfaces. | |
| task | Yes | Plain-English intent, e.g. 'find Apple's latest 10-K'. No URLs — intent, not destination. | |
| variants | No | Optional. Behavior facets when one matters: `{ auth_state: 'logged_in'|'logged_out', locale: 'en-US', region: 'EU', currency: 'USD' }`. Affects cache key — omit when uncertain. | |
| scopeHint | No | Optional. Only after a prior `ambiguous_scope` — pass one of `error.scope_options[].pattern` verbatim (leading slash, no trailing). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully describes behavior: how to handle each status, not to screenshot, read only DOM, confirm irreversible steps, and call report_outcome. It also details retry conditions.
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 well-structured, but slightly long. It front-loads purpose and organizes by status, making it clear. Minor redundancy could be trimmed.
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 no output schema, the description covers the return format via text and handles all states (success, failure, retry, skip) comprehensively, plus follow-up instructions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value with practical guidance like paths as implicit scope hints and caching behavior for variants.
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 the tool provides pre-computed navigation recipes for public websites and should be called before any browser action. It distinguishes itself from the only sibling 'report_outcome', which is a follow-up tool.
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 when to use (before any browser action on open web) and when to skip (localhost, search without destination). It also provides retry logic for specific errors.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
report_outcomeReport whether a Bowmark recipe ran cleanlyAInspect
Report whether the RECIPE ran cleanly — not whether you got the user a good answer. Call ONCE per envelope after you finished walking the recipe OR abandoned it.
success: true = every step executed AS WRITTEN. Each locator resolved on the first try, no extra clicks/scrolls/waits beyond the recipe, no JS-eval workarounds, no skipped steps, no substituted selectors. If you walked the recipe clean, report true — even if the answer turned out wrong (answer correctness is a separate concern).
success: false if ANY of these happened, even when you eventually helped the user: a locator missed, a click did nothing, you retried with a different selector, you fell back to raw browser code (browser_run_code_unsafe etc.), you scrolled or clicked extra to recover state, you skipped a step, the recipe led somewhere unexpected. Honest failures trigger a re-crawl that fixes the recipe; false true silently degrades it for everyone.
Quick check before reporting: if your tool-call sequence since the recipe started is longer than the recipe's step list, that's false. If you used raw browser code, that's false.
Skip when: ask returned a miss (no id); user interrupted mid-execution; you read the envelope but didn't execute it; task is still waiting on user input.
| Name | Required | Description | Default |
|---|---|---|---|
| success | Yes | True ONLY if the recipe ran clean — every step as written, no retries, no JS-eval fallbacks, no extra clicks. False on ANY deviation, even if the user got the right answer another way. | |
| evidence | Yes | REQUIRED on every call. Describe how the RECIPE behaved — NOT what you found for the user. `{ what_happened: string, error?: string, screenshot_id? }`. `what_happened` should name which steps ran clean and which needed retries/substitutions/JS-eval/extra clicks. ❌ 'Found restaurant X with 4.9 stars' (task outcome). ✅ 'All 6 steps ran as written' (clean). ✅ 'Steps 1-4 clean. Step 5 `All filters` locator missed; tried 3 selectors then used raw JS click. Step 6 never reached.' (hiccup). Re-crawl reads this to decide what to fix. | |
| envelope_id | Yes | `id` from a `status: ok` envelope. Miss envelopes have no `id`. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It fully explains what constitutes success ('every step executed AS WRITTEN') and failure, including detailed examples and a quick check rule. 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 thorough but well-structured with clear sections. Could be slightly more concise, but every sentence serves a purpose 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 3 parameters, all required, with nested object and no output schema, the description covers usage, meaning of success/failure, evidence format, and skip conditions comprehensively. No 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 coverage is 100% with descriptions for all parameters. The description adds significant context beyond schema, especially for 'evidence' with detailed examples and guidance on what to include, distinguishing recipe behavior from task outcome.
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 'whether the RECIPE ran cleanly — not whether you got the user a good answer', specifying a specific verb-resource pair and distinguishing it from the sibling 'ask'.
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?
Explicitly states when to call ('ONCE per envelope after you finished walking the recipe OR abandoned it') and when to skip ('ask returned a miss', 'user interrupted', etc.). Provides clear conditions for success vs failure.
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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