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 agentmods add commands/initialneil/project-with-reflect/log-and-reflectgit clone --depth 1 https://github.com/initialneil/project-with-reflectWrote 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/commands/initialneil/project-with-reflect/log-and-reflect)<a href="https://agentmods.dev/commands/initialneil/project-with-reflect/log-and-reflect"><img src="https://agentmods.dev/badge/commands/initialneil/project-with-reflect/log-and-reflect.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 | $0.00022 | $0.00320 |
| Opus 5 | $0.00011 | $0.00160 |
| Sonnet 5 | $0.00004 | $0.00064 |
| Haiku 4.5 | $0.00002 | $0.00032 |
Grade A, and why
log-and-reflect 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 5d 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.
What it actually says
Run the reflect action of the current project's project-with-reflect skill with arguments: $ARGUMENTS
Resolve the project from the current directory first: match $PWD against registry.json projects'
repo / dir (the project whose repo contains $PWD). If none matches, ask which project — don't
guess. (Same cwd→registry match the auto-log hook and /register-workstream use.) Then follow
<project_dir>/SKILL.md's reflect workflow.
reflect is already log-and-reflect: it captures this session first (appends key events not yet in
the log — to the active stream, or a connection's log if the finding is about a device/API), then
distills into lean lessons + decisions (run results → append-only lessons/experiment-*.md), refreshes
the dashboard, surfaces code-improvement flags, and
archives consumed logs. This command is just the muscle-memory name for it, callable from anywhere in the
repo without a /<project> prefix. Any $ARGUMENTS pass through: a <target> → directed reflect on a
code area / repo skill; --reground → full rewrite of one module.
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.
- 5d ago First seen · 19 lines · 22 tokens per session scan A a5b298aa5c76
log-and-reflect is a command published in the GitHub repository initialneil/project-with-reflect (13 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 320 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
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analyze-context
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cc-memory
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