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 FuRongJun-1999/dsh-memory --skill compiler-f8c8b24bgit clone --depth 1 https://github.com/FuRongJun-1999/dsh-memoryWrote 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/furongjun-1999/dsh-memory/compiler-f8c8b24b)<a href="https://agentmods.dev/skills/furongjun-1999/dsh-memory/compiler-f8c8b24b"><img src="https://agentmods.dev/badge/skills/furongjun-1999/dsh-memory/compiler-f8c8b24b/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/furongjun-1999/dsh-memory/compiler-f8c8b24b"><img src="https://agentmods.dev/badge/skills/furongjun-1999/dsh-memory/compiler-f8c8b24b.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 | $0.00097 | $0.00443 |
| Opus 5 | $0.00048 | $0.00221 |
| Sonnet 5 | $0.00019 | $0.00089 |
| Haiku 4.5 | $0.00010 | $0.00044 |
Grade A, and why
compiler-f8c8b24b 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 yesterday.
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
分析-信息差追踪（compiler-f8c8b24b）
When to use
任务「信息差追踪」；对照：智能论——信息差追踪（编译期信息差分析记录）。
克制条款（不适用条件）
events 为空/非法时；op 非 {latest, max, record} 时
How to execute
按 op 分派；顺序调用
Verification
- 单元样例 4 条（cases 断言）
- 物理基底：按 calibration 对照（编译/运行/断言裁决）
References
- 单元库：compiler_code_units.py「分析-信息差追踪」
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.
- yesterday First seen · 46 lines · 97 tokens per session scan A ce45e7f605c7
compiler-f8c8b24b is a skill published in the GitHub repository FuRongJun-1999/dsh-memory (164 stars, last pushed today), licensed MIT. It adds 97 tokens to every session and 443 once invoked, about $0.0005 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 2026-09-11.
Other skills, from other repositories
graphify
Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community…
potpie-source-ingestion
Use when the user explicitly asks to ingest, refresh, or deeply understand a repository, PR, issue, ticket, runbook, incident report, document, or web link into Potpie. The harness performs todo-driven discovery, uses local/GitHub/integration tools and read-only subagents when available, builds evidence-backed…
potpie-repo-baseline
Use when establishing, refreshing, or deeply understanding a repository's baseline memory in Potpie: purpose, application type, features, services/modules, environments, deploy shape, dependencies, API contracts, datastores, integrations, ownership, and explicit preferences. The harness reads authored and…
potpie-project-preferences
Use before writing, modifying, reviewing, refactoring, or testing code so repo/project preferences surface: error handling, file structure, frameworks, logging, dependency choices, testing, security, API style, and naming. Also use after code work when a reusable project preference should be recorded.
bcs-coordination
A coordination system for several software agents, meaning separate automated assistants, working together.
orchestrate
This skill should be used when the user asks to 'orchestrate a task', 'break down work into parallel agents', 'coordinate subtasks', 'run agents in parallel', or mentions 'multi-agent'. Decomposes complex tasks into tracked subtasks, dispatches parallel subagents, and coordinates until completion.