DeltaSignal ATLAS-7

DeltaSignal article TripCode generate

deltasignal_generate_article_tripcode

Read-onlyIdempotent

Use this read-only identity tool to generate a deterministic TF-SUB resolver object for a DeltaSignal-owned article or narrative research node. Parameters: primary issuer/ticker, title, research_slug, research_date, and optional research_version define the stable DeltaSignal identity. Substack post_id, canonical_url, slug, and published_at are publication metadata only and must not change the TripCode. Behavior: idempotent and local with no destructive side effects; it does not write Azure Blob, does not mutate Substack, and does not call wallets or x402 settlement. Use the returned TripCode in the article subtitle and the returned canonical blob paths in the authoring/sync pipeline.

Input Schema

TableJSON Schema

Name	Required	Description
`title`	Yes	Article title. Required for the article payload, but not hashed when research_slug is supplied.
`author`	No	Article author or publication author.
`issuer`	No	Primary issuer symbol when ticker is not supplied.
`ticker`	No	Primary issuer ticker. Alias for issuer/primary_issuer.
`post_id`	No	Optional Substack post ID. Secondary publication metadata only.
`platform`	No	Publication platform. Defaults to Substack.
`subtitle`	No	Article subtitle before TripCode writeback.
`publication`	No	Publication name. Defaults to DeltaSignal.
`research_id`	No	Optional explicit DeltaSignal research ID. If omitted, issuer + research_slug + research_date + version form the canonical identity.
`thesis_line`	No	Optional concise thesis line. Defaults to title.
`article_body`	No	Optional article body used only for content hash/provenance, not canonical TripCode identity.
`published_at`	No	Optional publication timestamp. Secondary publication metadata only.
`canonical_url`	No	Optional public canonical URL. Secondary publication metadata only.
`claim_summary`	No	Optional claim summary bullets.
`research_date`	Yes	Stable DeltaSignal research date in YYYY-MM-DD form.
`research_slug`	Yes	Stable DeltaSignal research slug, for example hut-8-re-rating-deadline.
`river_tripcodes`	No	Optional linked TF-RIVER TripCodes.
`research_version`	No	Optional research version. Defaults to 1.
`publication_state`	No	Optional article state such as draft or published_or_linked.
`linked_ds_tripcodes`	No	Optional linked TF-DS signal TripCodes.
`monitoring_checklist`	No	Optional monitoring checklist.
`linked_xbrl_tripcodes`	No	Optional linked TF-XBRL evidence TripCodes.
`invalidation_checklist`	No	Optional invalidation checklist.
`prior_article_tripcodes`	No	Optional prior TF-SUB TripCodes in this River.

Output Schema

TableJSON Schema

Name	Required	Description
`data`	Yes	Generated TF-SUB article/narrative research resolver object.
`provenance`	Yes	Traceability information for the MCP tool response.
`mcp_summary`	Yes	Concise high-signal summary of the tool response. Maximum 140 characters.
`usage_metadata`	No	Performance and estimated cost metadata for this MCP tool call.
`suggested_follow_ups`	Yes	Concrete next MCP calls an agent can run to continue the workflow.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

AddedJun 9, 2026
RemovedJun 8, 2026
AddedJun 8, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Beyond annotations (readOnly, idempotent, destructive=false), the description adds valuable behavior: 'idempotent and local with no destructive side effects', specifics about what it does not affect (Azure Blob, Substack, wallets, x402 settlement), and a key determinism constraint (publication metadata 'must not change the TripCode'). These details go well beyond the annotations and enrich the operational understanding.

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

Conciseness5/5

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

The description is a single dense paragraph that front-loads the purpose, then covers parameter roles, behavioral guarantees, and usage of outputs. Every sentence contributes substantive information, and the length is justified by the tool's complexity (24 parameters). No redundant filler.

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 tool's complexity, the description covers purpose, parameter semantics, behavioral boundaries, and output usage ('Use the returned TripCode in the article subtitle and the returned canonical blob paths...'). The presence of an output schema means detailed return values need not be listed. The description, combined with the schema and annotations, provides a complete operational picture.

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 has 100% coverage with per-parameter descriptions, but the description adds meaningful grouping: it distinguishes identity-defining parameters (issuer/ticker, title, research_slug, research_date, research_version) from publication metadata (post_id, canonical_url, slug, published_at) and stresses that metadata must not affect the TripCode. This semantic grouping is not fully evident in the schema, adding real value.

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 clearly states the tool's function: 'generate a deterministic TF-SUB resolver object' for a DeltaSignal-owned article or narrative research node. It uses a specific verb (generate) and resource (TF-SUB resolver object), and the focus on 'identity tool' distinguishes it from sibling tools like resolve or list tripcodes.

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: 'Use this read-only identity tool' and explains how to use the output ('Use the returned TripCode in the article subtitle...'). It also lists what the tool does not do (write Azure Blob, mutate Substack, call wallets/x402 settlement), but does not explicitly name alternative sibling tools for resolution or listing. Thus it provides good context but no explicit exclusions or alternatives.

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

B3.1/5.0

Disambiguation2/5

Significant overlap exists between atlas7_* and deltasignal_* tools for the same concepts (covenant stress, readiness, peer ranking, morning brief, pressure board), and composite workflows coexist with their low-level components. The descriptions are detailed but the sheer number of similar-scope tools makes misselection likely.

Naming Consistency4/5

Most tools follow a consistent lower_snake_case pattern with a domain prefix (atlas7_, deltasignal_, strategix_). Verb-first names (generate_, resolve_, search_) and noun-only names (alpha_opportunities, readiness) are both used, but the convention is predictable enough to navigate.

Tool Count1/5

With 81 tools, the surface is far beyond the 25–50 range considered excessive. Many tools are composites, natural-language variants, or near-duplicates that could be consolidated, creating an extreme mismatch for typical MCP server scope.

Completeness4/5

The tool surface is extensive, covering fundamentals, covenant stress, alpha screening, peer ranking, daily changes, briefs, historical ATLAS data, TripCode resolution, perp factors, synthetic ETF audit, and StrategiX rendering. Minor gaps exist (watchlist persistence, thesis lifecycle), but core research workflows are well covered.

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