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 guanyang/open-agent-hub --skill filesystem-contextgit clone --depth 1 https://github.com/guanyang/open-agent-hubWrote 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/guanyang/open-agent-hub/filesystem-context)<a href="https://agentmods.dev/skills/guanyang/open-agent-hub/filesystem-context"><img src="https://agentmods.dev/badge/skills/guanyang/open-agent-hub/filesystem-context.svg" alt="Measured on agentmods" 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 | $0.00049 | $0.03151 |
| Opus 5 | $0.00024 | $0.01576 |
| Sonnet 5 | $0.00010 | $0.00630 |
| Haiku 4.5 | $0.00005 | $0.00315 |
Grade A, and why
filesystem-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 7d 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.
This is a copy
100% identical to filesystem-context — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Filesystem-Based Context Engineering
Use the filesystem as the primary overflow layer for agent context because context windows are limited while tasks often require more information than fits in a single window. Files let agents store, retrieve, and update an effectively unlimited amount of context through a single interface.
Prefer dynamic context discovery -- pulling relevant context on demand -- over static inclusion, because static context consumes tokens regardless of relevance and crowds out space for task-specific information.
When to Activate
Activate this skill when:
- Tool outputs are bloating the context window
- Agents need to persist state across long trajectories
- Sub-agents must share information without direct message passing
- Tasks require more context than fits in the window
- Building agents that learn and update their own instructions
- Implementing scratch pads for intermediate results
- Terminal outputs or logs need to be accessible to agents
Do not activate this skill for adjacent work owned by other skills:
- Semantic cross-session memory, entity tracking, or temporal knowledge graphs:
memory-systems. - Conversation summarization, compaction, or durable handoff wording:
context-compression. - Token-efficiency tactics that do not require file-backed storage:
context-optimization. - Multi-agent topology or handoff protocol design:
multi-agent-patterns.
Core Concepts
Diagnose context failures against these four modes, because each requires a different filesystem remedy:
- Missing context -- needed information is absent from the total available context. Fix by persisting tool outputs and intermediate results to files so nothing is lost.
- Under-retrieved context -- retrieved content fails to encapsulate what the agent needs. Fix by structuring files for targeted retrieval (grep-friendly formats, clear section headers).
- Over-retrieved context -- retrieved content far exceeds what is needed, wasting tokens and degrading attention. Fix by offloading bulk content to files and returning compact references.
- Buried context -- niche information is hidden across many files. Fix by combining glob and grep for structural search alongside semantic search for conceptual queries.
What ships with it
2 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.
- 7d ago First seen · 297 lines · 49 tokens per session scan A bbde98d3481f
filesystem-context is a skill published in the GitHub repository guanyang/open-agent-hub (959 stars, last pushed today), licensed MIT. It adds 49 tokens to every session and 3,151 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to filesystem-context, differing in 0 lines, and is treated as a copy.
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