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DeltaSignal ATLAS-7

by io.github.aitrailblazer

DeltaSignal Morning Brief Natural Language brief

deltasignal_morning_brief_natural
Read-onlyIdempotent

Use this premium read-only Natural Language tool when the user wants the server-composed Morning Brief rendered as audit-grade Markdown. It compiles backend-composed compact evidence across readiness, daily changes, risk distribution, top stressed issuers, and alpha opportunities. The renderer never fans out into tools and never generates social drafts or trade recommendations. Parameters: style is professional, concise, trader, or detailed. Date and limit are accepted only where the backend composite supports them. Behavior: read-only and idempotent; it performs the server-enforced Morning Brief workflow, has no destructive side effects, then renders the returned compact evidence as a bounded Natural Language response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoOptional compact record limit where supported.
styleNoRendering style. Style changes tone and density only, not facts.
periodNoOptional YYYY-MM-DD date selector when supported by the backend composite.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesNatural Language Morning Brief response rendered from backend-composed compact evidence.
provenanceYesTraceability information for the MCP tool response.
mcp_summaryYesConcise high-signal summary of the tool response. Maximum 140 characters.
usage_metadataNoPerformance and estimated cost metadata for this MCP tool call.
suggested_follow_upsYesConcrete next MCP calls an agent can run to continue the workflow.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds value by detailing the workflow: 'performs the server-enforced Morning Brief workflow', 'no destructive side effects', and 'renders the returned compact evidence as a bounded Natural Language response'. It also highlights key behavioral constraints (never fans out, no social drafts/trade recommendations), going beyond the structured annotations. 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.

Conciseness4/5

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

The description is front-loaded with the primary purpose and then structured into parameters and behavior. It is somewhat verbose with minor redundancy ('read-only' appears in the first line and in the behavior section, 'no destructive side effects' echoes annotations), but every sentence contributes essential context.

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?

Given the presence of an output schema, annotations, and a rich parameter schema, the description covers purpose, use cases, behavioral constraints, and parameter semantics adequately. It does not detail the output format, but the output schema likely accounts for that. The description is sufficiently complete for an agent to select and invoke the tool correctly.

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 each parameter described. The description adds semantic nuance by explaining that 'style changes tone and density only, not facts' and that 'Date and limit are accepted only where the backend composite supports them', which clarifies conditional behavior not fully evident from the schema alone.

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-resource pairing: 'Use this premium read-only Natural Language tool when the user wants the server-composed Morning Brief rendered as audit-grade Markdown.' It clearly distinguishes itself from sibling tools (e.g., deltasignal_morning_brief) by emphasizing 'Natural Language' and 'never fans out into tools', and lists the content areas it compiles (readiness, daily changes, risk distribution, top stressed issuers, alpha opportunities).

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 explicitly states when to use the tool ('when the user wants the server-composed Morning Brief rendered as audit-grade Markdown') and provides exclusions ('never fans out into tools and never generates social drafts or trade recommendations'). It does not name alternative sibling tools explicitly, but the context signals and the exclusions make the intended use clear.

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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TDQS

C2.8/5.0
Disambiguation2/5

The tool set has extensive overlap: natural-language variants duplicate raw JSON tools (e.g., deltasignal_covenant_stress vs deltasignal_covenant_stress_natural), composite workflow tools duplicate low-level screens (deltasignal_alpha_sweep vs deltasignal_alpha_opportunities), and the atlas7_* and deltasignal_* prefixes repeat the same concepts (e.g., atlas7_covenant_stress vs deltasignal_covenant_stress). An agent would likely struggle to pick the right tool for a given intent.

Naming Consistency2/5

Three distinct prefixes (atlas7_, deltasignal_, strategix_) are used, and duplicate tool names appear across prefixes (e.g., atlas7_readiness vs deltasignal_readiness). Verb patterns are inconsistent, mixing nouns and verbs (atlas7_archive_search, deltasignal_thesis_create, deltasignal_morning_brief_natural), and there is no clear rule for raw, natural, composite, or resolver variants.

Tool Count1/5

With 81 tools, the server is massively over-scoped. Many are near-duplicates or overlapping composites; the core domain likely needs 20-30 tools at most. The count is far beyond what an agent can reasonably navigate, and it indicates a failure to consolidate or version the surface.

Completeness3/5

The set covers a broad range of functionality: screening, stress, alpha, peer comparison, history, tripcode resolution, synthetic ETF state, and thesis monitoring. However, there are lifecycle gaps (e.g., thesis_create has no corresponding update/delete, and the atlas7 vs deltasignal split leaves no unified surface). The duplication suggests comprehensive coverage in some areas and awkward holes in others.

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