review-reminder-format

review-reminder-format is an agent for Claude Code from uphy/obsidian-reminder. It costs 63 tokens per session (695 once invoked), scanned A, original, MIT.

Reviews a diff of obsidian-reminder for reminder-syntax correctness — parsing and rewriting in src/model/format, round-trips, compatibility with the Tasks/Kanban/Dataview formats, recurrence, done/cancelled handling. Used by the pr-review workflow; read-only.

Agent for Claude Code

Written for Claude Code: installed under .claude/.

Install with agentmods
npx agentmods add agents/uphy/obsidian-reminder/review-reminder-format
Install

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.

Clone the repo
git clone --depth 1 https://github.com/uphy/obsidian-reminder

Made for: Claude Code.

Wrote 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.

agentmods badge for review-reminder-format

README.md
[![agentmods](https://agentmods.dev/badge/agents/uphy/obsidian-reminder/review-reminder-format/github.svg)](https://agentmods.dev/agents/uphy/obsidian-reminder/review-reminder-format)
Your own site
<a href="https://agentmods.dev/agents/uphy/obsidian-reminder/review-reminder-format"><img src="https://agentmods.dev/badge/agents/uphy/obsidian-reminder/review-reminder-format/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.

agentmods 80×15 button for review-reminder-format

Your own site · 80×15
<a href="https://agentmods.dev/agents/uphy/obsidian-reminder/review-reminder-format"><img src="https://agentmods.dev/badge/agents/uphy/obsidian-reminder/review-reminder-format.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 63 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 695 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00063 $0.00695
Opus 5.5 $0.00025 $0.00278
Sonnet 5.5 $0.00013 $0.00139
Haiku 4.5 $0.00006 $0.00069

Measured today against content hash 8294909669ff, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

review-reminder-format 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 today.

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.

.claude/agents/review-reminder-format.md · 53 lines

How it starts

The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You review one perspective of a change to obsidian-reminder: whether reminders are still parsed from, and written back to, Markdown correctly. You never edit files. Bash is for read-only commands and for running existing tests (mise exec -- npx jest <path>, mise exec -- npx jest -t "<name>") to check a hypothesis; never write or modify files, including temporary tests inside the repository.

What to look for

  • Round-trip safety
    • modifyReminder / toMarkdown() rewriting more of the line than the reminder it targets: losing other inline fields, emojis, block ids (^abc), trailing whitespace the user typed, indentation, \t.
    • Columns (columnStart/columnEnd) computed in a unit that differs from how they are consumed (UTF-16 code units vs. code points; emojis such as ⏰ 📅 🔁 ✅ ❌ are surrogate pairs, some with a variation selector).
  • Format interaction (CompositeReminderFormat tries each enabled format)
    • A line matched by two formats, or a change in one format's regex that starts or stops matching lines another format owns.
    • Behavior that depends on settings (custom emoji for the Tasks format, linking dates to daily notes, the primary format, time defaults) where the diff only handles the default settings.
  • Tasks plugin semantics — status characters beyond [ ]/[x], done date ✅, cancelled date ❌, scheduled/start/due precedence, recurrence 🔁 producing the next occurrence's date on completion.
  • Kanban/Dataview — cards have no checkbox; inline fields [key:: value] and (key:: value).
  • Markdown structure — reminders inside callouts (> - [ ]), nested list items, code blocks and frontmatter (must not be parsed), CRLF line endings.

Past incidents in this repository (use as calibration)

  • fix/tasks-cancelled-date: Tasks-format lines with a done or cancelled date were still treated as open reminders.
  • PR #384 (open): completing a recurring task lost the recurrence anchor and wrote the wrong date on the next occurrence.
  • #379: inserting a reminder into a Kanban card added a checkbox.
  • #359 (open): reminder pills are not shown for tasks inside callouts.

Read the full file on GitHub · 53 lines

Changes

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.

  1. today First seen · 53 lines · 63 tokens per session scan A 8294909669ff

Subscribe to this mod's changes

review-reminder-format is an agent published in the GitHub repository uphy/obsidian-reminder (664 stars, last pushed today), licensed MIT. It adds 63 tokens to every session and 695 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-10-21.

Related

Other agents, from other repositories

ml_engineer

Machine learning engineering specialist for designing, training, evaluating, and shipping production ML models. Use when the task requires feature pipeline design, model training code, evaluation harnesses, or integrating models into application code. For example: building a classifier training pipeline, wiring a…

josstei/maestro-orchestrate · 70 tokens

mlops_engineer

MLOps specialist for model registry, CI/CD for models, deployment, monitoring, and drift detection. Use when the task requires packaging models for serving, building training/deploy pipelines, configuring model monitoring, or wiring up canary rollouts. For example: automating retraining on a schedule, setting up…

josstei/maestro-orchestrate · 76 tokens

data-engineer

Data engineering specialist for schema design, query optimization, ETL pipelines, and data modeling. Use when the task involves database migrations, query performance tuning, data pipeline construction, or schema evolution. For example: designing a normalized schema, optimizing slow queries, or building a data…

josstei/maestro-orchestrate · 61 tokens

ml-engineer

Machine learning engineering specialist for designing, training, evaluating, and shipping production ML models. Use when the task requires feature pipeline design, model training code, evaluation harnesses, or integrating models into application code. For example: building a classifier training pipeline, wiring a…

josstei/maestro-orchestrate · 70 tokens

mlops-engineer

MLOps specialist for model registry, CI/CD for models, deployment, monitoring, and drift detection. Use when the task requires packaging models for serving, building training/deploy pipelines, configuring model monitoring, or wiring up canary rollouts. For example: automating retraining on a schedule, setting up…

josstei/maestro-orchestrate · 76 tokens

geo-routing-engineer

Geospatial and routing specialist for Product-Builder products with maps, scheduling-by-location, or vehicle routing (route-optimization in logistics, dispatch in home services, field-booking). Owns the routing contract — geocoding, the VRP/routing model (constraints, objective), maps/distance-matrix provider…

avelikiy/great_cto · 112 tokens