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/lpalbou/agorahub/backlognpx skills add lpalbou/AgoraHub --skill backloggit clone --depth 1 https://github.com/lpalbou/AgoraHubWrote 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/lpalbou/agorahub/backlog)<a href="https://agentmods.dev/skills/lpalbou/agorahub/backlog"><img src="https://agentmods.dev/badge/skills/lpalbou/agorahub/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 5.1 | $0.00099 | $0.01694 |
| Opus 5 | $0.00049 | $0.00847 |
| Sonnet 5 | $0.00020 | $0.00339 |
| Haiku 4.5 | $0.00010 | $0.00169 |
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 5d 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Backlog System
Use the backlog as durable planning memory, not as authority over the code. Keep enough history that a later agent can answer what was built, what is next, what was considered, what should not be built, why priorities changed, and what evidence proved completion.
Start With The Right Pass
- If asked to create a backlog system from scratch, read
references/layout-and-templates.mdfirst and establish the directory layout, overview, and recurrent tasks before adding many items. - If asked to add or revise a backlog item, inspect the current code and docs first. Then read
references/layout-and-templates.mdfor the correct item shape. - If asked to complete or deprecate work, read
references/maintenance-checklists.mdfirst so history, ledgers, links, and follow-ups are preserved. - If asked to clean up, normalize, triage, or sync the backlog, run the hygiene and follow-up
flows in
references/maintenance-checklists.md.
Apply The Operating Rules
- Read the repository before writing backlog text. Treat stale backlog text as a bug.
- Keep every item standalone enough for a future agent to execute without the original chat.
backlogowns work-item lifecycle, planning state, and implementation history.adrowns durable cross-task policy.- Separate committed work from speculative work:
planned/for intended implementation work.proposed/for plausible but uncommitted ideas, risks, or experiments.completed/for closed audit records.deprecated/for superseded, rejected, or indefinitely deferred work.recurrent/for periodic process tasks.
- Keep one durable overview that records counts, priorities, next recommended work, ledgers, and operating rules.
- Every backlog item file must start with a four-digit global ID prefix:
NNNN_<slug>.md. This is mandatory acrossplanned/,proposed/,completed/,deprecated/, and topic subfolders. A number such as0044should identify one durable backlog item for search and references. - Do not put dates in backlog item filenames. Dates belong inside item metadata such as
Created,Completed,Deprecated, or completion reports. - Preserve history instead of rewriting it away. Move items across states and append reports; do not silently replace earlier intent.
- Cross-reference relevant ADRs, docs, code, tests, and related backlog items.
- If a backlog item creates a rule that should outlive the task, do not leave that rule buried in backlog prose. Create or update an ADR before closure, or record explicit ADR state explaining why not.
- When creating or updating an ADR from backlog work, use the
adrskill when available and keep the ADR reader-first: title, status,Context, thenDecisionbefore optional metadata. - Use topical subfolders when several backlog items form one larger track.
planned/<topic>/...andproposed/<topic>/...are valid when the topic README explains the track and the main overview still indexes the items. - Prefer one focused problem per item. Split oversized items instead of hiding multiple decisions inside one file.
- Record explicit validation expectations. A backlog item is not done because code changed; it is done because required behavior and evidence landed.
- After completion, review residual risks, open questions, optimization ideas, documentation gaps, and architecture insights. Preserve only the useful signals.
- Tell the user when backlog and code disagree, and patch the backlog before implementation unless the user explicitly overrides that process.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 123 lines · 99 tokens per session scan A f4103ef4eaab
backlog is a skill published in the GitHub repository lpalbou/AgoraHub (2 stars, last pushed today), licensed MIT. It adds 99 tokens to every session and 1,694 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 2026-08-31.
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