progress-guardian

Manages implementation progress using a plan + worklog + learn model: long-term plan in localdocs/plan. .md, future pre-plan items in localdocs/backlog. .md, phase/session logs in localdocs/worklog.todo.md, localdocs/worklog.doing.md, localdocs/worklog.done.md, and learning notes in localdocs/learn. .md.

Agent for Claude Code

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.

agentmods
npx agentmods add agents/tae0y/python-project-template/progress-guardian
Clone the repo
git clone --depth 1 https://github.com/tae0y/python-project-template

Made for: Claude Code.

Per session 90 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,991 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00090 $0.01991
Opus 5 $0.00045 $0.00996
Sonnet 5 $0.00018 $0.00398
Haiku 4.5 $0.00009 $0.00199

Measured today against content hash 999e50e0eb2a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

progress-guardian 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/progress-guardian.md · 281 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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 · 281 lines · 90 tokens per session scan A 999e50e0eb2a

Subscribe to this mod's changes

progress-guardian is an agent published in the GitHub repository tae0y/python-project-template (14 stars, last pushed 24d ago), with no licence file. It adds 90 tokens to every session and 1,991 once invoked, about $0.0005 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 2026-09-01.

Related

Other agents, from other repositories

pr-update-expert

Expert agent for updating GitHub PRs through optimized AI workflow. Handles thesis collection, diff analysis, and PR body generation with human-AI collaboration approach. Examples: Context: User wants to update their PR with latest changes. user: '/aiupdatepr' assistant: 'I'll use the pr-update-expert agent to update…

dagster-io/dagster · 184 tokens

code-standards-enforcer

Use this agent when you need to audit changed files for compliance with coding standards defined in CLAUDE.md. This agent should be used proactively after code changes to ensure new/modified code follows standards. Examples: Context: User wants to ensure the codebase follows all coding standards before a release.…

dagster-io/dagster · 252 tokens

agent-coach

Use this agent when you want to analyze and improve agent performance after any agent invocation. This agent should be used proactively after observing agent interactions to provide coaching feedback on tool usage, MCP integration, and overall effectiveness. Examples: Context: User has just used a code-review agent to…

dagster-io/dagster · 213 tokens

code-reviewer

Review PRs against this checklist. Be concise - only comment on actual issues.

sirsjg/flux · 0 tokens

star-auditor

Blind second read of finished work against a rubric — scores it, decides nothing, and was not present for the conversation that produced it.

wanghao9610/STAR · 31 tokens

star-collector

Read-only collection pass for a STAR skill — reads the exact files it was given and returns the form it was given, filled in.

wanghao9610/STAR · 30 tokens