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 skills/masonegger/bpe-claude-code-plugin/session-summarynpx skills add MasonEgger/bpe-claude-code-plugin --skill session-summarygit clone --depth 1 https://github.com/MasonEgger/bpe-claude-code-pluginWhat 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 | $0.00016 | $0.01179 |
| Opus 5 | $0.00008 | $0.00589 |
| Sonnet 5 | $0.00003 | $0.00236 |
| Haiku 4.5 | $0.00002 | $0.00118 |
Grade A, and why
session-summary 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 2d 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Session Summary Command
Create a complete session summary and capture lessons learned. This command performs two actions:
- Generates a session summary file in
.ai-sessions/ - Appends lessons learned to
.ai-sessions/lessons.md
Step 1: Load the Format Reference and Setup
Read the canonical format reference at ${CLAUDE_PLUGIN_ROOT}/references/session-management.md. Treat that file as the single source of truth for templates, naming conventions, and lesson capture guidance; do not restate or reinterpret its rules in this command.
If .ai-sessions/ does not exist, create it:
mkdir -p .ai-sessions
Generate the timestamp using this exact command:
date +%Y%m%d-%H%M
Step 2: Generate Session Summary
Create .ai-sessions/session-{timestamp}-{slug}.md per the naming convention and section template in the format reference ("Session Summary Template" section).
Populate every required section. Pull content from this conversation:
- Header metadata (date, duration, conversation turns, estimated cost, model)
- Goal Context (only if a
/goalran in this session, per "Goal Context Populating Rule" in the reference; omit the section entirely otherwise) - Key actions taken
- Prompt inventory (table of user prompts → actions → outcomes)
- Efficiency insights, process improvements, observations
- Suggested skills for next session (which skills the next
/bpe:execute-planshould invoke at its hardened skill-loading step; see "Suggested Skills Populating Rule" in the reference)
If .ai-sessions/implementation-notes.md exists and contains a ## Step <N> section for the step this summary covers, extract its bullets and add a ## Deviations from Plan section to the session summary with them.
Then remove that ## Step N section from implementation-notes.md: keep the file if other sections remain, else delete the file.
The entry format (- Plan said: <what> / - Deviated: <what actually happened> / - Impact: <consequence> under a ## Step N heading) is defined in the format reference ("implementation-notes.md Format" section).
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.
- 2d ago First seen · 84 lines · 16 tokens per session scan A 948809137124
session-summary is a skill published in the GitHub repository MasonEgger/bpe-claude-code-plugin (7 stars, last pushed 10d ago), licensed MIT. It adds 16 tokens to every session and 1,179 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 2026-08-31.
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