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.
git clone --depth 1 https://github.com/chrismbryant/claude-journal-mcpWrote 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/chrismbryant/claude-journal-mcp/journal-time)<a href="https://agentmods.dev/commands/chrismbryant/claude-journal-mcp/journal-time"><img src="https://agentmods.dev/badge/commands/chrismbryant/claude-journal-mcp/journal-time/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/commands/chrismbryant/claude-journal-mcp/journal-time"><img src="https://agentmods.dev/badge/commands/chrismbryant/claude-journal-mcp/journal-time.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00000 | $0.00612 |
| Opus 5 | $0.00000 | $0.00306 |
| Sonnet 5 | $0.00000 | $0.00122 |
| Haiku 4.5 | $0.00000 | $0.00061 |
Grade A, and why
journal-time 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 12d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Time-Based Journal Query
You are helping the user query journal entries by time period.
This command uses natural language time expressions to find entries.
Process
-
Understand the time query: User might ask in various ways:
- "What did I work on last week?"
- "Show me entries from January"
- "When did I implement feature X?"
- "What happened yesterday?"
-
Extract time expression: Supported formats:
- Relative: "yesterday", "today", "last week", "last month", "last year"
- Recent periods: "last 3 days", "last 2 weeks"
- Current periods: "this week", "this month", "this year"
- Month names: "january", "january 2024"
- ISO dates: "2024-01-15"
-
Use the MCP tool: Call
journal_time_query:journal_time_query( time_expression="last week", query="optional search terms" (if looking for something specific), project="project-name" (optional) ) -
Present results:
- Show entries within the time range
- Highlight what they accomplished
- Group by day or week if many results
- Summarize patterns or themes
Examples
Example 1: Recent past
User: "What did I do last week?"
→ journal_time_query(time_expression="last week")
→ Present all entries from last week
Example 2: Specific search in time range
User: "When did I work on authentication?"
→ journal_time_query(time_expression="last month", query="authentication")
→ Find auth-related entries from last month
Example 3: Historical lookup
User: "Show me what I did in January"
→ journal_time_query(time_expression="january")
→ All January entries
Example 4: Project timeline
User: "What have I done on my-api this year?"
→ journal_time_query(time_expression="this year", project="my-api")
Presentation Format
Present with time context:
**Journal Entries: Last Week** (15 found)
Week of Jan 8-14, 2024
Monday, Jan 8:
- [45] Implemented OAuth login (my-app)
- [44] Set up testing framework
Tuesday, Jan 9:
- [43] Fixed cache memory leak
...
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.
- 12d ago First seen · 94 lines · 0 tokens per session scan A cb1dbe54c8d3
journal-time is a command published in the GitHub repository chrismbryant/claude-journal-mcp (6 stars, last pushed 7mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 612 tokens. 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.
Other commands, from other repositories
review-epo-claims
Analyze patent claims for EPO Art. 84 EPC compliance - clarity, conciseness, support by description.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
resume
Auto-detect and resume any interrupted Plan Cascade task. Detects mega-plan, hybrid-worktree, or hybrid-auto context and routes to the appropriate resume command.
infinite
INFINITE AGENTIC LOOP COMMAND.
github-modes
This document describes all GitHub integration modes available in Claude-Flow with ruv-swarm coordination. Each mode is optimized for specific GitHub workflows and includes batch tool integration for maximum efficiency.
checklist
Generate a custom checklist for the current feature based on user requirements.