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/codebloodedai/claude-code-ops-commandsWrote 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/codebloodedai/claude-code-ops-commands/planner-link)<a href="https://agentmods.dev/commands/codebloodedai/claude-code-ops-commands/planner-link"><img src="https://agentmods.dev/badge/commands/codebloodedai/claude-code-ops-commands/planner-link/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/codebloodedai/claude-code-ops-commands/planner-link"><img src="https://agentmods.dev/badge/commands/codebloodedai/claude-code-ops-commands/planner-link.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 | $0.00022 | $0.01026 |
| Opus 5.5 | $0.00009 | $0.00410 |
| Sonnet 5.5 | $0.00004 | $0.00205 |
| Haiku 4.5 | $0.00002 | $0.00103 |
Grade A, and why
planner-link 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 2mo 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run this ONCE (or when adding new tasks) to bootstrap the Planner ↔ CLAUDE.md join keys. After this runs, /planner-pull and /planner-push can find every bullet deterministically.
Step 1: Get your Planner user ID
az rest --method GET --url "https://graph.microsoft.com/v1.0/me?\$select=id,displayName"
Step 2: Pull tasks from all 3 active plans
Same as /planner-pull step 2. For each task, extract: id, title, percentComplete, planId.
Plan IDs (authoritative list — source of truth is ~/CLAUDE.md "Microsoft Planner Reference"):
- IT Operations:
<YOUR_PLAN_ID_1> - Enterprise Engineering & Operations:
<YOUR_PLAN_ID_2> - AI Initiatives:
<YOUR_PLAN_ID_3>
Filter to tasks assigned to you OR with no assignee (orphans should be flagged).
Step 3: Read ~/CLAUDE.md and extract existing bullets
Read ~/CLAUDE.md. For every line matching:
- [ ] <text> `(<owner>)` `<pct>%` [optional trailing — comment]
- [x] <text> `(<owner>)` ...
capture: line number, checkbox state, full text, owner, pct, whether it already has a <!-- planner:... --> anchor.
Step 4: Match bullets to tasks
For each strategy bullet without an anchor, score every Planner task by text similarity against the bullet's text. Use a simple approach:
- Normalize both to lowercase, strip punctuation, drop stopwords (the, a, an, to, of, for, in, on, and)
- Compute token overlap / Jaccard similarity
- Prefer tasks in the same "domain" — bullets under OBJ-1 sections are more likely to match IT Operations plan tasks, OBJ-4 bullets match Enterprise Engineering
For each bullet, keep the top 3 candidate matches with their similarity scores.
Step 5: Show the proposed mapping
Display a table like:
BULLET → CANDIDATE MATCHES
(L45) Ship monitoring integration (you) 10% → 1. "Monitoring integration" (95%) [IT Ops] <EXAMPLE_TASK_ID>
→ 2. "SIEM Implementation" (42%) [IT Ops] bB-67cfwJE-VYOw...
→ 3. (no other candidates above 30%)
(L52) Harden password manager posture (you) 75% → 1. "improve password security posture" (88%) [IT Ops] <EXAMPLE_TASK_ID_2>
→ 2. "Integrate password manager with Azure SSO" (40%) [IT Ops] 2AusZtjQ-UaGdW...
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.
- 2mo ago First seen · 85 lines · 22 tokens per session scan A f09bc8395232
planner-link is a command published in the GitHub repository codebloodedai/claude-code-ops-commands (2 stars, last pushed 6mo ago), licensed MIT. It adds 22 tokens to every session and 1,026 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
vs-queue
Show what is waiting on the operator, then the live / in-flight board tasks.
complete
Review implementation evidence and plan the spec completion transaction.
anchors
List what each requirement tag anchors to (read-only).
check-task.en
Check a task's current status and progress.
init-milestones.en
Initialize the repository's standard milestones taxonomy.
next
Suggest the most likely next workflow action based on current context.