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 skills add DevExpress/agent-skills --skill devexpress-wpf-grid-datasourcegit clone --depth 1 https://github.com/DevExpress/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/devexpress/agent-skills/devexpress-wpf-grid-datasource)<a href="https://agentmods.dev/skills/devexpress/agent-skills/devexpress-wpf-grid-datasource"><img src="https://agentmods.dev/badge/skills/devexpress/agent-skills/devexpress-wpf-grid-datasource/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/devexpress/agent-skills/devexpress-wpf-grid-datasource"><img src="https://agentmods.dev/badge/skills/devexpress/agent-skills/devexpress-wpf-grid-datasource.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00096 | $0.02552 |
| Opus 5.5 | $0.00038 | $0.01021 |
| Sonnet 5.5 | $0.00019 | $0.00510 |
| Haiku 4.5 | $0.00010 | $0.00255 |
Grade A, and why
devexpress-wpf-grid-datasource 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 3d ago.
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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Step 1 — Learn the decision criteria
Read references/source-selection.md for its decision tree — the signals (data origin, update frequency, data volume) that map onto each destination family. Don't select a source yet; this is only so Step 2's inspection knows which points to spot and highlight.
Step 2 — Inspect
Spawn inspect (see Subagent protocol). It finds the GridControl/TreeListControl/View target (or reports none exists), classifies the three signals per references/code-inspection.md, and returns a files-of-interest list.
Skip delegation only when no sub-agent/subtask dispatch tool exists at all, or the target and signals are already known from earlier in this conversation — then inspect inline using references/code-inspection.md yourself. This fallback is scoped to this step only — it never extends to Steps 5/6 (see there).
Step 3 — Ask only what's unresolved
Ask about any signal inspect left unresolved — one question at a time via a structured tool if available (AskUserQuestion, Copilot's askQuestions), inline chat otherwise. State what was inferred from code first. If the developer already stated a signal in their request, treat it as known — never re-ask it.
Step 4 may not begin until every signal is resolved — answered by the developer, or already known from code/request. An unresolved signal (Data Volume most often, since references/code-inspection.md treats it as ask-only by default) is a hard stop here, not a value to carry forward and default. Mentioning the assumption to the developer after generating code is not a substitute for asking before — if you catch yourself about to write "I'm assuming X rows" instead of asking, that is this step being skipped; go back and ask instead.
Step 4 — Select the source
Apply source-selection.md's decision tree (read in Step 1) to map (origin, frequency, volume) onto a destination family and its pinned doc URL(s). Every input to the tree must already be a resolved value from Step 2/3 — never feed it an unresolved signal (see the tree's own note on this).
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 65 lines · 96 tokens per session scan A e61df834d265
devexpress-wpf-grid-datasource is a skill published in the GitHub repository DevExpress/agent-skills (66 stars, last pushed 4d ago), licensed MIT. It adds 96 tokens to every session and 2,552 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-10-20.
Other skills, from other repositories
TEMPLATE
../../../agents/personas/TEMPLATE.md.
amazon-location-service
Integrates Amazon Location Service APIs for AWS applications. Use this skill when users want to add maps (interactive MapLibre or static images); geocode addresses to coordinates or reverse geocode coordinates to addresses; calculate routes, travel times, or service areas; find places and businesses through text…
amplify-workflow
Build and deploy full-stack web and mobile apps with AWS Amplify Gen2 (TypeScript code-first). Covers auth (Cognito), data (AppSync/DynamoDB including schema modeling, enum types, relationships, authorization rules), storage (S3), functions, APIs, and AI (Amplify AI Kit with Bedrock). Supports React, Next.js, Vue…
aws-lambda-durable-functions
Build resilient, long-running, multi-step applications with AWS Lambda durable functions with automatic state persistence, retry logic, and orchestration for long-running executions. Covers the critical replay model, step operations, wait/callback patterns, error handling with saga pattern, testing with…
api-gateway
Build, manage, and operate APIs with Amazon API Gateway (REST, HTTP, and WebSocket). Triggers on phrases like: API Gateway, REST API, HTTP API, WebSocket API, custom domain, Lambda authorizer, usage plan, throttling, CORS, VPC link, private API. Also covers troubleshooting API Gateway errors (4xx, 5xx, timeout, CORS…
aws-lambda
Design, build, deploy, test, and debug serverless applications with AWS Lambda. Triggers on phrases like: Lambda function, event source, serverless application, API Gateway, EventBridge, Step Functions, serverless API, event-driven architecture, Lambda trigger. For deploying non-serverless apps to AWS, use…