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/mazen160/backlog/backlog-memorynpx skills add mazen160/backlog --skill backlog-memorygit clone --depth 1 https://github.com/mazen160/backlogWhat 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 | $0.00083 | $0.01417 |
| Opus 5 | $0.00042 | $0.00709 |
| Sonnet 5 | $0.00017 | $0.00283 |
| Haiku 4.5 | $0.00008 | $0.00142 |
Grade A, and why
backlog-memory 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.
How it starts
The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
backlog-memory
Two jobs, one skill:
- learn — read everything in a project (tasks, plans, docs, memory) into the current session. Read-only.
- store — synthesize the project's state into persistent memory entries, grouped by theme, so future sessions load context instantly.
Invocation
/backlog-memory— auto-pick the mode (see below), default project./backlog-memory <alias>— auto-pick the mode for that project./backlog-memory learn [alias]— force learn./backlog-memory store [alias]— force store.
Choosing the mode (when none is given)
An explicit learn / store always wins. Otherwise decide:
- Start of a fresh session / orienting — you've just started, little or no project context is loaded, the user wants to get up to speed → run learn.
- Work has been done this session — tasks were created, moved, or closed; plans or comments were added; decisions were made; the project state changed → run store to refresh the persisted summaries.
- Ambiguous / you can't tell — ask the user before doing anything: "Should I learn (load this project's context) or store (persist a fresh memory snapshot)?"
When you're unsure whether work has happened, check recent activity and use your judgment:
backlog activity --project <alias> --limit 20 --json --profile default
Recent writes by the current actor in this session lean toward store; a quiet log at the start of a session leans toward learn.
Resolve the project
backlog project list --json --profile default
Use the provided alias, or pick the project the user is actively working in. If it's genuinely unclear which project, ask.
Mode: learn (read into context)
The read phase — no writes.
1. Read everything in parallel
# Memory entries (decisions, architecture, context notes)
backlog memory list --project <alias> --json --profile default
# Docs list
backlog doc list --project <alias> --json --profile default
# Open tasks (todo + doing)
backlog task list --project <alias> --status todo --json --profile default
backlog task list --project <alias> --status doing --json --profile default
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 · 168 lines · 0 tokens per session scan A 1a1b5df28944
backlog-memory is a skill published in the GitHub repository mazen160/backlog (15 stars, last pushed 1mo ago), licensed MIT. It adds 83 tokens to every session and 1,417 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
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team-workflow
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importing-a-codebase
Use when the repo holds real source code but no specs: the existing-codebase branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for empty workspaces (starting-a-new-project) or feature work in a specced project (brainstorming).
starting-a-new-project
Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instead.
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todos
This chat has a shared, live TODO plan — your tasks for the conversation, which the user also edits. Read this skill and reach for the todo tools whenever a request takes more than a couple of steps. It covers the plan model (group = task, items = its steps; loose items are the user's lane), how to work it: propose…