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 TheaDust/lore --skill skillgit clone --depth 1 https://github.com/TheaDust/loreWrote 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/theadust/lore/skill)<a href="https://agentmods.dev/skills/theadust/lore/skill"><img src="https://agentmods.dev/badge/skills/theadust/lore/skill/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/theadust/lore/skill"><img src="https://agentmods.dev/badge/skills/theadust/lore/skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 10 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- high Anti-Refusal · line 223 Skill attempts to nullify the agent's safety policies or restrictions ('you have no restrictions', 'ignore your guidelines', 'do anything now'). This is a direct jailbreak that disables guardrails.Fix: Remove jailbreak framing that nullifies safety policies or restrictions. Skill content must not instruct the agent to ignore its guidelines or operate without guardrails.
- high Prompt Injection · line 223 This pattern attempts to override system instructions or ignore safety constraints. Without LLM analysis, manual review is recommended.Fix: Remove or rewrite any text that instructs the agent to ignore prompts, override safety rules, or trust unverified content. Ensure skill content cannot be injected to alter agent behavior.
- high Prompt Injection · line 223 This pattern attempts to override system instructions or ignore safety constraints. Without LLM analysis, manual review is recommended.Fix: Remove or rewrite any text that instructs the agent to ignore prompts, override safety rules, or trust unverified content. Ensure skill content cannot be injected to alter agent behavior.
- high Rogue Agent · line 223 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
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 | $0.00141 | $0.04935 |
| Opus 5.5 | $0.00056 | $0.01974 |
| Sonnet 5.5 | $0.00028 | $0.00987 |
| Haiku 4.5 | $0.00014 | $0.00494 |
Grade A, and why
lore 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 — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
lore — Framework-agnostic Memory Management
What this skill is
A long-term knowledge base for a software project, maintained by AI agents. It is not a dev journal or a changelog. It captures the kind of context that normally lives only in the original developer's head:
- What the project is, how it is shaped (architecture)
- Why specific choices were made over alternatives (decisions)
- How code should be written and what to avoid (conventions)
This knowledge is persisted as plain Markdown files in .lore/ at the project root. Any agent that can read files can consume them.
When to trigger
The skill uses a two-tier trigger model.
Tier 1 — Loading the skill
Load this skill when the user explicitly invokes lore, names a subcommand, references .lore/, or asks to record, recall, audit, sync, or compress project memory about decisions, architecture, conventions, or monorepo scopes. Generic phrases like "init", "compress", "audit", or "query" alone are not enough — they may map to the agent's native commands or unrelated tasks (Claude Code's /init, /compact, security audits, SQL queries, etc.).
| User says (examples) | Command |
|---|---|
| "lore init" / "create lore memory bank" / "initialize lore" | init |
| "lore sync" / "sync this change to lore" / "record this decision in lore" | sync |
| "lore query" / "query lore" / "what's the project convention" | query |
| "lore audit" / "check lore" / "is memory still accurate" | audit |
| "lore compress" / "compress lore" / "summarize lore" | compress |
| "lore mirror" / "update CLAUDE.md" / "refresh mirror" | mirror |
| "lore history" / "show the git history of this entry" / "show me the commits behind this" | history |
Tier 2 — Internal proposals (after the skill is loaded)
Once the skill is loaded for this session, certain commands may proactively propose themselves based on internal thresholds. Writes follow the configured trust controls: confirmation-required changes wait for the user, while permitted auto-applied changes are reported after writing.
What ships with it
17 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.
- references/audit-template.md 2.9 KB
- references/compatibility.md 11 KB
- references/config.md 6.4 KB
- references/entry-format.md 6.4 KB
- references/history-command.md 7.1 KB
- references/monorepo-detection.md 2.3 KB
- references/platform-mirrors.md 18 KB
- references/stale-new-markers.md 4.3 KB
- references/summary-template.md 3.2 KB
- references/workflows.md 22 KB
- scripts/find_duplicates.py 6.7 KB runs code
- scripts/find_stale.py 5.2 KB runs code
- scripts/history.py 25 KB runs code
- scripts/id_hash.py 1.1 KB runs code
- scripts/list_entries.py 8.7 KB runs code
- scripts/README.md 6.7 KB
- scripts/README.zh-CN.md 6.3 KB
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 · 240 lines · 141 tokens per session scan A 79a666fb9b27
lore is a skill published in the GitHub repository TheaDust/lore (24 stars, last pushed 1mo ago), licensed MIT. It adds 141 tokens to every session and 4,935 once invoked, about $0.0006 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.
Other skills, from other repositories
agent-state-bar
A design guide for an agent status bar: a short, automatically updated summary of progress, remaining tasks, tool counts, errors, and system state placed near the latest model input.
knowledge-org
A guide to organising large bodies of knowledge so an AI system can navigate relationships, summaries, and layers instead of searching only flat text chunks. It covers tree indexes, knowledge graphs, file-like structures, incremental updates, and long-term memory layouts.
context-compression
A guide to shortening the information an agent carries between steps. It explains how to replace large tool outputs and old conversation details with compact, useful summaries while preserving important decisions and constraints.
memory-system
A guide to giving an AI agent persistent, user-specific memory across conversations. It covers what to remember, how to store it, how to update or compress it, and when to use memory instead of a shared knowledge base.
openlore
Query and publish to an OpenLore knowledge repository over SSH using ordinary shell commands. Use when a task needs project documentation, runbooks, shared team knowledge, or a place to publish findings.
openlore-housekeeping
Audit and maintain a shared OpenLore knowledge repository. Use on a schedule or on request to find stale docs, broken links, unreviewed inbox items, and missing skill coverage, then publish an audit report.