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 commands/langerrr/zforge/plan-statusgit clone --depth 1 https://github.com/Langerrr/zforgeWhat 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 | $0.00008 | $0.00365 |
| Opus 5 | $0.00004 | $0.00182 |
| Sonnet 5 | $0.00002 | $0.00073 |
| Haiku 4.5 | $0.00001 | $0.00036 |
Grade A, and why
plan-status 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.
What it actually says
/plan-status — Workspace Feature Status
Scan for all feature plans under the current working directory and display their status.
Process
-
Search for all
05_progress_overview.mdfiles under the current working directory using Glob:**/docs/*/05_progress_overview.md -
For each found file:
- Extract the feature name from the directory path
- Read the file and parse the phase summary table and the Standing Flags section
- Count: total phases, completed, running, pending, and open standing flags
-
Display a summary table:
Feature Plans in {current_directory}:
Feature Status Progress Flags Path
────────────────────────────────────────────────────────────────
ai_assistant In Progress 3/5 phases — docs/ai_assistant/
video_pipeline In Progress 1/3 phases 1 open docs/video_pipeline/
api_refactor Complete 2/2 phases — docs/api_refactor/
A feature with every phase complete and an open standing flag is not Complete. Show it as Flagged with the flag count — the whole point of tracking flags is that they survive the run ending.
-
List open standing flags below the table, with the phase that opened each and what closes it.
-
If no
05_progress_overview.mdfiles are found, report: "No feature plans found under {current_directory}."
Scope
ONLY look under the current working directory. Do not search parent directories or sibling projects.
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 · 41 lines · 8 tokens per session scan A 80c0599c039d
plan-status is a command published in the GitHub repository Langerrr/zforge (10 stars, last pushed 2d ago), licensed MIT. It adds 8 tokens to every session and 365 once invoked, about $0.0000 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.
Other commands, from other repositories
issue-implement
Implement a specific stage of an issue's implementation plan using feature-dev.
issue-create
Create a structured GitHub issue from current context or description.
template
Manage issue templates for streamlined issue creation.
project-recap
Generate a visual project recap for context switching.
speckit.auto
Automatically execute the four core phases of the Spec-Driven Development (SDD) pipeline: specify → plan → tasks → implement, in strict sequential order.
daily-priorities
Query DIGI Jira via the Atlassian MCP to build a prioritized daily work plan. The report has two parts: suggested priorities (the recommendation) and full context (everything you need to evaluate whether the suggestions are right and what else is on the docket).