Bid/no-bid verdicts for open EU tenders, from 592,000 real TED contract awards.
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Average 4.4/5 across 4 of 4 tools scored.
Two tools (find_low_competition_lanes and find_winnable_lanes) are explicitly identical, with the latter deprecated. This creates confusion for an agent trying to select the correct tool, despite the deprecation note. The other two tools are distinct.
Tool names follow a verb_noun pattern (find_*, get_*, search_*), but find_winnable_lanes is a deprecated alias with a name that implies a win forecast, which contradicts its actual function. This inconsistency reduces clarity.
Four tools is well-scoped for a server focused on EU tender analysis and competition detection. Each tool serves a clear purpose, and the count feels appropriate for the domain without being excessive or insufficient.
The tool set covers the core workflow: identifying low-competition lanes, searching tenders with verdicts, and retrieving detailed verdicts. Minor gaps exist (e.g., no raw tender search without verdict), but overall the surface is sufficient for its research purpose.
find_low_competition_lanesARank CPV sector "lanes" by OBSERVED competition density from the full corpus of 530,000 real EU awards: median bidders, single-bidder share, bid-rate, median value, beachhead score. Answers "where is competition thinnest right now". It does NOT estimate the user's probability of winning — thin competition is a selection signal, not a win forecast. Returns the top-ranked lanes only (see "limit"); the total count is in coverage.lanes_ranked. Data/research tool over TED (Tenders Electronic Daily, CC BY 4.0). No guarantee of award.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many top-ranked lanes to return (sorted by beachhead_score) | |
| min_n | No | Drop lanes thinner than this (honest: small n = noise) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and destructiveHint, so the safety profile is clear. The description adds crucial context: it's a data/research tool over TED, no guarantee of award, returns only top lanes, and includes total count in coverage. 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 a single paragraph with no fluff. It front-loads the action and then explains scope and limitations. Every sentence serves a purpose. Could be slightly more structured but is efficient.
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?
With no output schema, the description only vaguely indicates the return (top-ranked lanes, total count in coverage.lanes_ranked). It mentions metrics but not the exact output structure. More detail on return format 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 description coverage is 100% and the description adds value by explaining the purpose of min_n ('Drop lanes thinner than this (honest: small n = noise)') and the limit's role. This enriches understanding 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 uses a specific verb ('Rank CPV sector lanes') and clearly states the resource and metrics. It distinguishes from siblings by explicitly noting it does not estimate win probability, differentiating from find_winnable_lanes.
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 tells when to use the tool ('where is competition thinnest right now') and what it does NOT do (win forecast), helping avoid misuse. It does not explicitly mention alternative tools or when to use them, but the contrast with win probability is strong guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_winnable_lanesADEPRECATED — use find_low_competition_lanes instead; this alias behaves identically and stays available for existing clients. The old name wrongly implied a win forecast: TendFeed measures observed competition density, not the probability that you win. Data/research tool over TED (Tenders Electronic Daily, CC BY 4.0). No guarantee of award.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many top-ranked lanes to return (sorted by beachhead_score) | |
| min_n | No | Drop lanes thinner than this (honest: small n = noise) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true and destructiveHint=false, and the description adds context about being a data/research tool with no award guarantee, clarifying that it measures competition density, not win probability. No contradiction.
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 concise, front-loaded with deprecation notice, and each sentence serves a purpose: deprecation, alternative, caveat, data source, disclaimer. 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 output schema, the description sufficiently explains the tool's return (top-ranked lanes by beachhead_score), data source (TED), and limitations. Complete for a simple read 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 coverage is 100% with parameter descriptions. The description adds minimal extra context ('sorted by beachhead_score', 'honest: small n = noise'), but does not significantly expand on 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 tool's purpose: it measures observed competition density from TED data. It explicitly notes deprecation and directs to the correct sibling tool, distinguishing itself from find_low_competition_lanes.
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 guidance: use find_low_competition_lanes instead; warns that the old name implied a win forecast which this tool does not provide. Includes data source and disclaimer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_verdictAPull one versioned verdict object by tender id (decision, score, per-channel evidence, price status, reason). Requires an API key (Authorization: Bearer cfm_live_…) with an active TendFeed subscription; without one you get a machine-readable key-required or subscription-required answer. Data/research tool over TED (Tenders Electronic Daily, CC BY 4.0). No guarantee of award.
| Name | Required | Description | Default |
|---|---|---|---|
| tender_id | Yes | Tender publication id |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly and non-destructive; description adds authentication requirements, error responses, data source attribution, and a disclaimer about award guarantee. No contradiction with 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?
Two concise, front-loaded sentences that efficiently convey purpose, prerequisites, and constraints without 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?
For a single-parameter tool, the description covers what it returns, authentication, data source, and limitations. No output schema needed; completeness is high.
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% and description repeats the parameter's purpose. No additional semantic detail 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?
Clearly states it pulls a single versioned verdict object by tender ID, listing specific fields (decision, score, etc.). Distinguishes from sibling tools like search_tenders and lane-finding 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?
Specifies required API key and subscription, and behavior when missing. Provides context on data source (TED) and disclaimer. Implicitly differentiates from siblings through focus on single verdict retrieval.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_tendersAOpen EU tenders with a bid/no-bid verdict (Worth-It score, reason, competition density, price corridor where robust, deadline, SME-fit). Filter by sector (CPV division), country (NUTS), SME-only, min score. Guests (no key) get the expired-tender board plus a live_matched count; an API key (Authorization: Bearer cfm_live_…) with an active TendFeed subscription unlocks the live, still-biddable board. Data/research tool over TED (Tenders Electronic Daily, CC BY 4.0). No guarantee of award.
| Name | Required | Description | Default |
|---|---|---|---|
| cpv | No | CPV division prefix, e.g. 45 (construction), 72 (IT), 33 (medical) | |
| nuts | No | Country prefix, e.g. DE, FR, PL | |
| limit | No | ||
| sme_only | No | ||
| min_score | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true and destructiveHint=false. The description adds behavioral context: data source (TED, CC BY 4.0), no guarantee of award, and different behavior for guests vs authenticated users. No contradictions with 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?
The description is concise with no redundant sentences. It front-loads the main output and adds access details, data source, and disclaimer in a well-structured way.
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 5 parameters and no output schema, the description covers key aspects: what is returned, filters, access levels, and limitations. It lacks mention of default ordering or pagination, but the limit parameter is covered.
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?
All 5 parameters have schema descriptions, so baseline is 3. The tool description repeats some filter semantics but does not add new meaning 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?
The description clearly states this tool searches for open EU tenders with verdict details (Worth-It score, reason, etc.) and lists specific filters. It distinguishes from siblings like find_low_competition_lanes by focusing on general search rather than specific analyses.
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 provides clear guidance on usage based on authentication: guests see expired tenders and a count, authenticated users see live tenders. It implies this tool is for exploring tenders, but does not explicitly exclude use cases for siblings.
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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