Skip to main content
Glama

Browse the B4 Index

b4_browse
Read-only

Search and filter the B4 Index's 1,600+ independently scored software categories. Browse by keyword, domain, quadrant, or industry. When filtering by industry, returns all vertical categories for that industry PLUS all horizontal categories (which apply to every industry). Each row carries its banded verdict — primary, confidence word, and a near-call flag — and the quadrant filter matches the verdict at whichever lens you are reading. Verdicts are banded (B4 methodology v4.0), not point calls: each of the three quadrant dimensions carries a ±1 uncertainty band, the resulting cells are enumerated exactly, and the verdict is the quadrant holding the most probability mass. Every verdict ships with its full distribution, a confidence word — clear (≥70% of the mass), lean (50–70%), split (<50%) — and a near-call flag when the runner-up is within 15 points. An axis counts as high only when it clears the 3.5 line strictly, which on this 1–5 grid means only at 4 or above, so a category sitting exactly on the line gets the safer call: ties break in the order BUY → BRIDGE → BEWARE → BUILD, cheapest mistake first. Optional org lens: set org to "small", "medium" (the default) or "large" to read the same scores as a team of that engineering maturity — it shifts the center of the AI-feasibility band by −1 / 0 / +1 and nothing else. The lens is a filter the caller looks through, never a stored profile: no user attribute is saved, inferred, or asked for, and the scores themselves never change. Omit it and you get the default-lens numbers, which are the ones published on logged-out surfaces.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgNoOrg-maturity lens: "small" (no dedicated engineering), "medium" (default — some AI capability), "large" (AI-mature). Shifts the AI-feasibility band center by −1/0/+1 at read time. A filter the caller looks through, never a stored profile.medium
limitNoMax results to return (default 20, max 100)
queryNoSearch term to match against category names, vendors, domains, and rationales
domainNoFilter by domain (e.g., 'Marketing Technology', 'CRM & Sales')
industryNoFilter by industry group. Returns matching vertical categories + all horizontal categories. Options: Healthcare, Financial Services, Construction & Real Estate, Education, Energy & Utilities, Government, Automotive, Agriculture, Transportation & Logistics, Media & Entertainment, Legal, Professional Services, Nonprofits & Associations, Manufacturing, Retail & Commerce, Hospitality & Food Service, Telecom
quadrantNoFilter by quadrant

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=true, but the description adds substantial behavioral detail: the banded verdict methodology, confidence words (clear/lean/split), near-call flags, tie-breaking order, and the org lens semantics (shifts band center, stored nowhere, does not change scores). This goes well beyond the annotation and fully informs the agent of edge behaviors and privacy-safe operations.

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

Conciseness4/5

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

The description is long but front-loaded with the primary purpose, then systematically explains the verdict system and edge cases. Every sentence earns its place given the methodological complexity, but the length is borderline for a simple browse tool and could be tightened without losing essential information.

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

Completeness4/5

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

The description covers the tool's behavior thoroughly, including output semantics (verdict, distribution, confidence, near-call) and the org lens, which compensates for the absence of an output schema. Minor gaps remain, such as an explicit statement of pagination or exact response format, but the essentials are present.

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 descriptive parameter entries, setting a baseline of 3. The description adds important context beyond the schema by explaining the org lens effect (−1/0/+1 shift, no persistence) and the quadrant tie-breaking rule (BUY→BRIDGE→BEWARE→BUILD), which are not in the schema. This added value justifies a 4.

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 leads with a specific verb+resource: 'Search and filter the B4 Index's 1,600+ independently scored software categories.' This clearly distinguishes browse from sibling tools like b4_audit, b4_compare, b4_recommend, and b4_score, which have different intents.

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

Usage Guidelines4/5

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

The description provides clear usage context by listing the axes to browse (keyword, domain, quadrant, industry) and the optional org lens. It does not explicitly contrast with alternatives, but the sibling names make differentiation obvious, and the behavior is well-scoped for browsing rather than auditing or scoring.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: browse discovers categories, recommend maps natural language to categories, score evaluates a single category, compare provides build-vs-buy analysis, and audit aggregates verdicts across a portfolio. The detailed descriptions eliminate ambiguity between overlap-adjacent tools like score and compare.

Naming Consistency5/5

All tools follow a consistent 'b4_<verb>' pattern with lowercase and underscores, making the action of each tool predictable. The verbs (audit, browse, compare, recommend, score) are distinct and match the tool's function.

Tool Count5/5

The 5-tool set is well-scoped for the B4 Index domain, covering discovery, evaluation, comparison, recommendation, and portfolio analysis without redundancy or bloat. Each tool provides a distinct value-add, and the count is within the ideal 3-15 range.

Completeness5/5

The set provides full lifecycle coverage for the B4 Index domain: users can browse categories, get natural-language recommendations, score a category, compare build vs. buy, and audit an entire stack. There are no obvious dead ends, and the optional org lens and evidence flag add depth without creating gaps.

Resources