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.
git clone --depth 1 https://github.com/thematters/matters-webWrote 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/rules/thematters/matters-web/data-fetching)<a href="https://agentmods.dev/rules/thematters/matters-web/data-fetching"><img src="https://agentmods.dev/badge/rules/thematters/matters-web/data-fetching/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/rules/thematters/matters-web/data-fetching"><img src="https://agentmods.dev/badge/rules/thematters/matters-web/data-fetching.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 | $0.00015 | $0.01600 |
| Opus 5.5 | $0.00006 | $0.00640 |
| Sonnet 5.5 | $0.00003 | $0.00320 |
| Haiku 4.5 | $0.00002 | $0.00160 |
Grade A, and why
data-fetching 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 1mo 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Fetching & State Management
Matters Web uses Apollo Client for GraphQL data fetching and state management.
GraphQL Structure
src/components/GQL/queries: Contains reusable GraphQL queriessrc/components/GQL/mutations: Contains reusable GraphQL mutations- Component-specific GraphQL operations are typically defined in a
gql.tsfile within each component directory
Apollo Client
The Apollo Client is configured in the app entry point (src/common/utils/apollo.ts). It utilizes a sophisticated setup involving multiple Apollo Links (e.g., for persisted queries, file uploads, retries, error handling, and context modification) to manage requests.
Key features include:
- Link Composition: Chains multiple links to handle concerns like authentication, fingerprinting, Sentry integration, and directing requests based on context (e.g., public vs. private queries).
- Cached Data Management: Leverages
InMemoryCachewith customresolversandtypePolicies(includingmergeables) for fine-grained control over how data is stored and merged. Uses fragment matching (introspectionQueryResultData) for accurate caching of polymorphic types. - Error Handling: Uses
onErrorlink for centralized logging of GraphQL and network errors. - Authentication Management: Conditionally includes credentials based on operation context.
Cache Management
Apollo Client provides powerful caching capabilities that help optimize performance and user experience. There are 3 main approaches to update the cache:
- Automatic Updates: Apollo automatically updates the cache for entities with matching IDs
- Refetching Queries: Force refetch queries after mutations to ensure fresh data
- Manual Updates: Directly modify the cache for complex scenarios
1. Automatic Updates
const TOGGLE_PIN = gql`
mutation TogglePin($id: ID!, $pinned: Boolean!) {
editArticle(input: { id: $id, pinned: $pinned }) {
id
pinned
}
}
`
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.
- 1mo ago First seen · 167 lines · 15 tokens per session scan A 36460b256646
data-fetching is a cursor rule published in the GitHub repository thematters/matters-web (86 stars, last pushed 5d ago), licensed Apache-2.0. It adds 15 tokens to every session and 1,600 once invoked, about $0.0001 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 2026-08-30.
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