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 parisgroup-ai/imersao-ia-setup --skill context-maintenancegit clone --depth 1 https://github.com/parisgroup-ai/imersao-ia-setupWrote 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/parisgroup-ai/imersao-ia-setup/context-maintenance)<a href="https://agentmods.dev/skills/parisgroup-ai/imersao-ia-setup/context-maintenance"><img src="https://agentmods.dev/badge/skills/parisgroup-ai/imersao-ia-setup/context-maintenance/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/parisgroup-ai/imersao-ia-setup/context-maintenance"><img src="https://agentmods.dev/badge/skills/parisgroup-ai/imersao-ia-setup/context-maintenance.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 | $0.00075 | $0.00955 |
| Opus 5 | $0.00037 | $0.00477 |
| Sonnet 5 | $0.00015 | $0.00191 |
| Haiku 4.5 | $0.00007 | $0.00096 |
Grade A, and why
context-maintenance 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 12d 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Maintenance
Audits all Claude context sources (memory files, CLAUDE.md, AGENTS.md) against the actual codebase to find and fix stale information. Prevents wrong context from persisting across conversations.
Problem This Solves
Claude loads memory files and AGENTS.md at session start. If these contain outdated information (wrong model IDs, missing services, stale counts), every conversation starts with incorrect assumptions — leading to wrong suggestions, wasted debugging, and repeated mistakes.
When to Use
- Starting a session after >7 days away from the project
- After changing configurations, services, or infrastructure
- After adding/removing features, API routes, or packages
- User asks to check context freshness
- You notice memory says X but code says Y
Checks
Run in parallel where possible. Adapt to the project's structure.
1. Memory Index Health
wc -l MEMORY.md → must be < 100 lines
MEMORY.md should be a concise index with links to topic files — not inline content. If over limit, extract content into topic files.
2. Memory vs Code Drift
For each memory topic file:
- Identify claims about code (model names, file counts, service lists, API configurations)
- Verify against actual code using Grep/Glob
- Flag discrepancies as DRIFT
Common drift sources:
- Service/function/endpoint counts and lists
- Model or library version references
- File paths that were moved or renamed
- Configuration values that changed
3. AGENTS.md Completeness
For each AGENTS.md in the project:
- Compare documented services/features against actual directory listings
- Check counts match reality (e.g., "15 functions" vs
ls | wc -l) - Verify listed tools/models match what code actually uses
4. Stale Topic Files
For each file in memory/:
- Check
descriptionfield still matches content - Flag files older than 30 days for review
- Verify no content duplicates what's already in AGENTS.md
- Check "Known Issues" — verify they still exist in code
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.
- 12d ago First seen · 111 lines · 75 tokens per session scan A 185ac8cabc0c
context-maintenance is a skill published in the GitHub repository parisgroup-ai/imersao-ia-setup (1 stars, last pushed 29d ago), licensed MIT. It adds 75 tokens to every session and 955 once invoked, about $0.0004 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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