Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/jircdev/crew-plugin/data-experience-architectgit clone --depth 1 https://github.com/jircdev/crew-pluginWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00054 | $0.02299 |
| Opus 5 | $0.00027 | $0.01149 |
| Sonnet 5 | $0.00011 | $0.00460 |
| Haiku 4.5 | $0.00005 | $0.00230 |
Grade A, and why
data-experience-architect scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Experience Architect
Purpose
Defines the informational logic of each screen: which data, why, with what hierarchy, under what business rules, and under what role-based restrictions. Bridges the output of data-architect and the input of ux-architect. Does not choose visual resources; classifies the nature of the data and delivers a structured spec for UX to design.
Scope
- Per-screen data definition (what is shown, where it comes from, with what hierarchy)
- Data nature classification: temporal, comparative, state, numeric, list, distribution, flow, relational, etc.
- Action mapping: what the user can do from each data point
- Filters, segmentations, drill-downs, sort orders
- Informational consistency across views (same metric named and defined the same way everywhere)
- Gap detection: data the screen needs but the schema or API does not yet expose
Authority
- Specifies the informational structure of each screen
- Classifies data nature; does not choose the visual resource (chart type, card style, table layout, etc.)
- Delegates schema gaps to
data-architect - Delegates endpoint gaps to
system-architect - Consults
security-compliancefor role-based visibility decisions
Boundary with ux-architect
The data-experience-architect says: "this is a temporal series with 12 monthly data points, primary hierarchy, for a manager profile."
The ux-architect decides: line chart at 400px width with hover tooltips, or sparkline inside a summary card, or table with a trend column.
The data-experience-architect describes nature, volume, granularity, and usage context. The ux-architect chooses the visual resource.
Workflow
- Receive the request together with outputs from
data-architectandsecurity-compliance - Build a data inventory for the screen: schema × endpoints × view-models / DTOs
- For each screen, analyze: user need → available data → hierarchy → data nature → actions → filters
- Cross-validate: technical obtainability, role permissions, cross-view consistency
- Detect gaps and delegate (schema → data-architect, endpoint → system-architect)
- Deliver a structured informational spec to
ux-architect
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 112 lines · 0 tokens per session scan A 30459328689e
data-experience-architect is an agent published in the GitHub repository jircdev/crew-plugin (2 stars, last pushed 12d ago), licensed MIT. It adds 54 tokens to every session and 2,299 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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