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 ai-analyst-lab/ai-analyst --skill maintain-contextgit clone --depth 1 https://github.com/ai-analyst-lab/ai-analystWrote 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/ai-analyst-lab/ai-analyst/maintain-context)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/maintain-context"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/maintain-context/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/ai-analyst-lab/ai-analyst/maintain-context"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/maintain-context.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 | $0.00045 | $0.00816 |
| Opus 5.5 | $0.00018 | $0.00326 |
| Sonnet 5.5 | $0.00009 | $0.00163 |
| Haiku 4.5 | $0.00005 | $0.00082 |
Grade A, and why
maintain-context 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 18d 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.
What it actually says
Maintain context
Read docs/CONNECTED-CONTEXT.md for the implemented commands and storage contract.
Resolve the actual context source, inspect its catalog and look for existing resources before adding another.
- Clarify audience, meaning, scope, source and owner. Ask about missing business rules rather than inventing policy. Guides explain meaning; queries give reviewed examples; models/metrics supply supported executable relationships and calculations. Keep guide prose in business terms: populations, qualifying behavior, units, time rules, exclusions and limitations. Plain-language formulas are appropriate. Physical table/column mappings belong in dataset documentation or semantic models; keys/joins in models and relationships; executable expressions in metrics or reviewed SQL. Do not expand a guide into a technical recipe just to make an evaluation pass. This is our architecture choice, not a universal restriction on all context products.
- Read
templates/semantic/<kind>.yamlfor a model, metric or relationship; usetemplates/guide.yamlortemplates/query.yamlfor guides or approved SQL entries. Scaffold a draft without overwriting:python -m helpers.connected_context --dataset DATASET scaffold KIND ID. Do not create a duplicate source document by default. Models, metrics and relationships are separate resources within one semantic layer, stored indatasets/DATASET/semantic/{models,metrics,relationships}/. Measures and dimensions belong inside models. Only add relationships when models need to join. Query entries reference reviewed SQL files, not saved metric requests; call metrics directly. - Fill the draft and typed references. A guide can be the owner-reviewed business definition itself.
If based on an existing company document, keep that document in its original system and record
optional
source_referenceswith its title, URL, owner, actual reviewed_on date and version if known. These citations are not automatically fetched or monitored; never invent a source or inspection. In guides, userefsfor required local dependencies (or an empty list) andimplementationsfor optional metric/query links; business approval does not approve the linked code. Calculations implementing a guide reference it throughrefs; review the guide before its models and metrics. The guide's optional reverse implementation link is not a dependency cycle. Reuse model/metric IDs. Keep evaluator expected outputs out of context. Review calculations independently and ask before executing queries if not already authorized. - Run the installed
validatecommand. Show meaning and implementation changes separately and stop for the user's review. Passing tests do not approve a business policy. Before review, inspect the actual guide prose for field mappings, join instructions or code. Verify complete business meaning survived and implementation links are accurate. Validation alone does not check this separation. Preserve displaced technical facts in their proper resources, and never report old evaluation passes as evidence for revised guide content. - Only after explicit approval, use
review KIND ID --reviewer PERSON --approval-note NOTE --reviewed-on DATE --review-after DATE. Record the real decision; do not fabricate a reviewer or note to make a draft executable. Review dependencies first. No publishing without authorization. - Test the resource and a nearby question where its rule does not apply. Preserve earlier results. Distinguish observed use, correctness and regression evidence; live/model tests need authority.
For migration, preview first and inspect legacy callers. Preserve the Session 7 definition and personal
context. Source/formula edits invalidate dependent reviews: do not silently refresh hashes. Unapproved
resources stay draft. Existing context improvements and before/after evals use /improve-context.
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.
- 18d ago First seen · 52 lines · 45 tokens per session scan A 78692bfade1f
maintain-context is a skill published in the GitHub repository ai-analyst-lab/ai-analyst (309 stars, last pushed 18d ago), licensed MIT. It adds 45 tokens to every session and 816 once invoked, about $0.0002 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 2026-10-01.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Optimize the meaningful UI available immediately from a Next.js route on an initial load (hard navigation) or named client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route and entry point at a time; the shipped test then guards…