Skip to main content
Glama
azmartone67

DC Hub — Data Center & Energy Intelligence

Deal Autopsy

deal_autopsy
Read-onlyIdempotent

Reveal the real play behind data-center M&A deals: overlay DCPI grid-reality verdicts to classify each as long-dated land/power option, near-term build, or queue gamble.

Instructions

Tracked data-center M&A / capex deal flow with the DCPI grid-reality verdict overlaid on each deal market — "what is the real play?". Returns recent deals (buyer, seller, value, market) + each market DCPI verdict and time-to-power; with a paid key, the per-deal autopsy read (long-dated land/power option vs near-term build vs queue gamble). Progressive disclosure to keep the default cheap: by default each read ships only a comparables COUNT (the verdict text is always included); pass comparables="summary" for the top-2 grounding signals, or comparables="full" to expand the complete cited set for a deal you're drilling into. Try: deal_autopsy limit=15.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of recent deals to return (default ~15)
comparablesNoComparables detail: "none" (default — count only, cheapest), "summary" (top-2 grounding signals), or "full" (the complete cited set). Escalate only for deals you're drilling into.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
quotaNoCaller quota state (remaining calls, tier) when available.
_entityNoPayload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.
citationNoMachine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload. Normally an OBJECT {source, url, license, cite_as, retrieved_at}; a bare string is accepted and carries the attribution line itself.
provenanceNoCollection-level provenance block: {source, method, as_of, verification_counts, cite_url_template, license, cite_as}. Quote the verification level when citing.
_front_doorNoIn-band front-door hint (first workflow-entry tool of a session): call plan_query(intent) first for the ordered multi-step plan.
_return_loopNoSuggested next-session delta call (get_changes since=24h) so you pull only what changed.
site_evaluation_handoffNoPre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries.
Behavior5/5

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

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses the paid-key requirement for per-deal autopsy reads, the progressive disclosure of comparables (count-only by default), and that the verdict text is always included. These are behavioral traits not captured in annotations or schema.

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 dense but every sentence carries weight—purpose, return fields, paid-tier behavior, progressive disclosure, and an example. It is front-loaded with the core function, though a bit jargon-heavy. It earns its length for a tool with this complexity.

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?

Given the output schema exists, the description need not detail return structures, yet it explains the key return elements and the pricing/progressive disclosure behavior. It provides a complete picture for an agent to select and invoke the tool, including the example call and escalation guidance.

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?

The schema already covers both parameters with descriptions (100% coverage), but the description adds practical meaning: the comparables parameter's escalation behavior, the default count-only mode, and an example invocation. This goes beyond the schema's baseline by clarifying the cost/benefit tradeoff.

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 opens with a specific verb and resource: 'Tracked data-center M&A / capex deal flow' and clearly states what it returns—recent deals (buyer, seller, value, market) plus a DCPI verdict and time-to-power. This distinguishes it from sibling tools like 'hyperscaler_deals' or 'list_transactions' by focusing on the DCPI 'grid-reality' overlay.

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 gives clear context on when to use the tool and how to escalate comparables detail ('Escalate only for deals you're drilling into'). It does not explicitly contrast with alternatives, but the purpose is well-scoped and the example ('Try: deal_autopsy limit=15') shows practical usage.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/azmartone67/dchub-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server