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 skills/lwalden/aiagentminder/backlognpx skills add lwalden/AIAgentMinder --skill backloggit clone --depth 1 https://github.com/lwalden/AIAgentMinderWrote 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/skills/lwalden/aiagentminder/backlog)<a href="https://agentmods.dev/skills/lwalden/aiagentminder/backlog"><img src="https://agentmods.dev/badge/skills/lwalden/aiagentminder/backlog.svg" alt="Measured on agentmods" 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 | $0.00008 | $0.00725 |
| Opus 5 | $0.00004 | $0.00362 |
| Sonnet 5 | $0.00002 | $0.00145 |
| Haiku 4.5 | $0.00001 | $0.00072 |
Grade A, and why
backlog 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 3d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/aiagentminder:backlog - Backlog Management
Capture future work items quickly, review the backlog, or promote items to the roadmap.
All file I/O goes through backlog-capture.sh — never read or edit BACKLOG.md directly.
Determine the Mode
The user's input will indicate one of three modes:
A) Capture (default)
The user wants to record a future work item. Parse their intent into:
- type:
defect,feature,spike, orchore - title: one-line summary
- source: where the idea came from (default:
session)
Then run:
backlog-capture.sh add <type> "<title>" "<source>"
If the type is ambiguous, pick the best match — don't ask. Use these heuristics:
- Bug, broken, error, regression →
defect - Investigate, evaluate, research, explore →
spike - Add, build, support, enable →
feature - Clean up, update, migrate, rename →
chore
If the user provides multiple items at once, run add for each one.
Optionally, if the user provided context beyond a title, also run:
backlog-capture.sh detail <id> "<context>"
Report the assigned ID(s) back to the user.
B) Review
The user wants to see and assess the current backlog. Run:
backlog-capture.sh list
backlog-capture.sh count
Present the items grouped by type. For each item older than 30 days (compare the Added date to today), flag it as stale.
Suggest promotions: items that align with the current roadmap phase or upcoming sprint work are good candidates. Items that have been stale for 60+ days should be considered for dropping.
C) Promote
The user wants to move a backlog item to the roadmap or into a sprint. Run:
backlog-capture.sh promote <id>
The script outputs the removed row. Use the row data to:
- If promoting to roadmap: apply
/aiagentminder:revisemechanics to add the item to the appropriate phase indocs/strategy-roadmap.md. - If pulling into the active sprint: add a row to SPRINT.md (with user confirmation, per scope-guardian rules).
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.
- 3d ago First seen · 91 lines · 8 tokens per session scan A 1130a9727e2f
backlog is a skill published in the GitHub repository lwalden/AIAgentMinder (4 stars, last pushed 1mo ago), licensed MIT. It adds 8 tokens to every session and 725 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 skills, from other repositories
sdd-workflow
Guide a project with Spec-Driven Development (SDD) discipline - idea, approved spec, consistent plan, tasks, a gate that verifies approval and consent, implementation, validation, and logbook. Bilingual EN/ES. Use when the user wants to start, spec, plan, implement, or validate work with SDD, or mentions specs, plans…
task-manager
Capture actionable user requests as persistent tasks, update task status as work progresses, and keep a shared task store in sync. Use when a user asks an agent to do work, check progress, block a task, complete a task, or manage the Kanban board.
todo
Maintain a shared workspace TODO list with blocked tasks.
linear-tools
Linear project management expert for issues, cycles, projects, and workflow automation.
project-manager
Project management expert for Agile, estimation, risk management, and stakeholder communication.
jira
Jira project management expert for issues, sprints, workflows, and reporting.