memory-log-render
Generate a human-readable Markdown view from a consumer's JSON Lines event log
Best use case
memory-log-render is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
It is a strong fit for teams already working in Codex.
Generate a human-readable Markdown view from a consumer's JSON Lines event log
Teams using memory-log-render should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/memory-log-render/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How memory-log-render Compares
| Feature / Agent | memory-log-render | Standard Approach |
|---|---|---|
| Platform Support | Codex | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Generate a human-readable Markdown view from a consumer's JSON Lines event log
Which AI agents support this skill?
This skill is designed for Codex.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# memory-log-render Convert a consumer's `.log.jsonl` into a readable `log.md` Markdown file. The rendered view uses greppable line prefixes and groups events by date. ## When to Use - On demand: user asks "show me the log" or "render the activity log" - After bulk operations: post-ingest or post-lint when the log has grown - As part of `memory-lint --fix`: regenerate the rendered view if stale ## Parameters ### --consumer (optional) Consumer ID. Resolved via ADR-021 D4 precedence: explicit > wrapper > auto-detect. ### --tail (optional, default: all) Only render the last N entries. Useful for large logs. ### --since (optional) Only render entries after this ISO 8601 date. ### --output (optional) Override output path. Defaults to sibling of `.log.jsonl` → `log.md` (e.g., `.aiwg/research/.log.jsonl` → `.aiwg/research/log.md`). ## Operation 1. **Resolve consumer** — determine which log to render. 2. **Load topology** — read `memory.topology.log` path from consumer's `manifest.json`. 3. **Read JSONL** — parse each line as JSON. Skip malformed lines (warn in output). 4. **Group by date** — cluster entries by `ts` date portion. 5. **Render Markdown** — for each entry, produce: ```markdown ## [2026-04-14] ingest | anthropic-2024-constitutional.pdf Touched 3 pages: anthropic.md, constitutional-ai.md, summaries/2024-constitutional-ai.md. Duration: 14.2s. No contradictions. ``` 6. **Write output** — overwrite the `log.md` file (this is a generated view, not an append). 7. **Log event** — append a `log-render` entry to `.log.jsonl` via `memory-log-append`. ## Rendered Format ```markdown # Memory Log — research-complete > Generated from `.aiwg/research/.log.jsonl` on 2026-04-14T16:00:00Z > 47 events total --- ## [2026-04-14] ingest | paper.pdf Touched 3 pages: entities/anthropic.md, concepts/constitutional-ai.md, summaries/paper.md. Duration: 14.2s. No contradictions. ## [2026-04-14] lint | health check 0 errors, 2 warnings, 5 suggestions. Duration: 3.4s. ## [2026-04-13] query-capture | Constitutional AI comparison Created synthesis/constitutional-ai-comparison.md (comparison). Added 2 cross-references. --- *Rendered by memory-log-render* ``` ## Line Prefix Convention Every operation line starts with `## [YYYY-MM-DD] <op> | <subject>` — this makes the rendered log greppable: ```bash grep "^## \[" .aiwg/research/log.md | tail -5 grep "ingest" .aiwg/research/log.md ``` ## Schema Reference @semantic-memory/schemas/memory-log-event.md
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