Bitterbot is a local-first personal AI agent that runs on a user’s devices, keeps persistent memories, performs tasks, and can exchange reusable skills with other agents. It is intended for people who want a personal assistant that remains available across conversations and activities. The catalogue entries provide instructions and agents for working with Bitterbot.
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 Bitterbot-AI/bitterbot-desktop --skill session-logsgit clone --depth 1 https://github.com/Bitterbot-AI/bitterbot-desktopWrote 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/bitterbot-ai/bitterbot-desktop/session-logs)<a href="https://agentmods.dev/skills/bitterbot-ai/bitterbot-desktop/session-logs"><img src="https://agentmods.dev/badge/skills/bitterbot-ai/bitterbot-desktop/session-logs.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 5.1 | $0.00020 | $0.00998 |
| Opus 5 | $0.00010 | $0.00499 |
| Sonnet 5 | $0.00004 | $0.00200 |
| Haiku 4.5 | $0.00002 | $0.00100 |
Grade A, and why
session-logs 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 8d 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.
This is a copy
81% identical to session-logs — 50 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
session-logs
Search your complete conversation history stored in session JSONL files. Use this when a user references older/parent conversations or asks what was said before.
Trigger
Use this skill when the user asks about prior chats, parent conversations, or historical context that isn't in memory files.
Location
Session logs live at: ~/.bitterbot/agents/<agentId>/sessions/ (use the agent=<id> value from the system prompt Runtime line).
sessions.json- Index mapping session keys to session IDs<session-id>.jsonl- Full conversation transcript per session
Structure
Each .jsonl file contains messages with:
type: "session" (metadata) or "message"timestamp: ISO timestampmessage.role: "user", "assistant", or "toolResult"message.content[]: Text, thinking, or tool calls (filtertype=="text"for human-readable content)message.usage.cost.total: Cost per response
Common Queries
List all sessions by date and size
for f in ~/.bitterbot/agents/<agentId>/sessions/*.jsonl; do
date=$(head -1 "$f" | jq -r '.timestamp' | cut -dT -f1)
size=$(ls -lh "$f" | awk '{print $5}')
echo "$date $size $(basename $f)"
done | sort -r
Find sessions from a specific day
for f in ~/.bitterbot/agents/<agentId>/sessions/*.jsonl; do
head -1 "$f" | jq -r '.timestamp' | grep -q "2026-01-06" && echo "$f"
done
Extract user messages from a session
jq -r 'select(.message.role == "user") | .message.content[]? | select(.type == "text") | .text' <session>.jsonl
Search for keyword in assistant responses
jq -r 'select(.message.role == "assistant") | .message.content[]? | select(.type == "text") | .text' <session>.jsonl | rg -i "keyword"
Get total cost for a session
jq -s '[.[] | .message.usage.cost.total // 0] | add' <session>.jsonl
Daily cost summary
for f in ~/.bitterbot/agents/<agentId>/sessions/*.jsonl; do
date=$(head -1 "$f" | jq -r '.timestamp' | cut -dT -f1)
cost=$(jq -s '[.[] | .message.usage.cost.total // 0] | add' "$f")
echo "$date $cost"
done | awk '{a[$1]+=$2} END {for(d in a) print d, "$"a[d]}' | sort -r
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.
- 8d ago First seen · 116 lines · 20 tokens per session scan A d4b931c5d867
session-logs is a skill published in the GitHub repository Bitterbot-AI/bitterbot-desktop (2,459 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 998 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to session-logs, differing in 50 lines, and is treated as a copy.
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