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 rjmurillo/ai-agents --skill memory-documentarygit clone --depth 1 https://github.com/rjmurillo/ai-agentsWrote 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/rjmurillo/ai-agents/memory-documentary)<a href="https://agentmods.dev/skills/rjmurillo/ai-agents/memory-documentary"><img src="https://agentmods.dev/badge/skills/rjmurillo/ai-agents/memory-documentary/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/rjmurillo/ai-agents/memory-documentary"><img src="https://agentmods.dev/badge/skills/rjmurillo/ai-agents/memory-documentary.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Prompt Injection · line 19 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00098 | $0.01345 |
| Opus 5.5 | $0.00039 | $0.00538 |
| Sonnet 5.5 | $0.00020 | $0.00269 |
| Haiku 4.5 | $0.00010 | $0.00135 |
Grade A, and why
memory-documentary 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 22d 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 — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Documentary Skill
Generate comprehensive documentary-style reports from your memory systems with full evidence chains.
Quick Start
/memory-documentary [topic]
Example topics:
- "recurring frustrations"
- "coding patterns not codified"
- "evolution of thinking on testing"
- "decisions I second-guessed"
- "what I complain about most"
Triggers
Use this skill when:
Search my memories for patterns about...What does my history say about...Generate a documentary on my topicCross-reference all systems for...Evidence-based analysis across memory systems
When to Use
Use this skill when:
- You need cross-system evidence for a pattern or recurring theme
- Investigating historical decisions and their evolution over time
- Building a cited, verifiable narrative from memory data
Use memory skill instead when:
- You need a simple search for a known fact or pattern
- The query targets a single memory tier, not cross-system synthesis
Quick Reference
| Phase | Action | Output |
|---|---|---|
| 1 | Topic Comprehension | Search variants, scope boundaries |
| 2 | Investigation Planning | Explicit queries per system |
| 3 | Data Collection | Evidence with retrieval keys and dates |
| 4 | Report Generation | Documentary with citations |
| 5 | Memory Updates | Store meta-pattern discovered |
Process
The skill searches ALL available data sources systematically:
Memory Systems (3 MCP servers):
- Claude-Mem: Timeline observations via 3-layer workflow
- Serena: Project-specific lexical memory
- DeepWiki: Documentation resources
What ships with it
1 file 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.
- 22d ago Changed · +5 lines 6eb3adac5aa5
- 24d ago Changed e5cfd5865507
- 1mo ago Changed · -1 lines · -3 tokens per session a2197c0c6261
- 1mo ago Changed · -1 lines 01a600fed5a4
- 1mo ago First seen · 215 lines · 101 tokens per session scan A 69555ae6a31b
memory-documentary is a skill published in the GitHub repository rjmurillo/ai-agents (48 stars, last pushed today), licensed MIT. It adds 98 tokens to every session and 1,345 once invoked, about $0.0004 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 2026-09-03.
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