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 skills add jpicklyk/task-orchestrator --skill review-proposalsgit clone --depth 1 https://github.com/jpicklyk/task-orchestratorWrote 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/jpicklyk/task-orchestrator/review-proposals)<a href="https://agentmods.dev/skills/jpicklyk/task-orchestrator/review-proposals"><img src="https://agentmods.dev/badge/skills/jpicklyk/task-orchestrator/review-proposals/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/skills/jpicklyk/task-orchestrator/review-proposals"><img src="https://agentmods.dev/badge/skills/jpicklyk/task-orchestrator/review-proposals.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00129 | $0.04202 |
| Opus 5 | $0.00064 | $0.02101 |
| Sonnet 5 | $0.00026 | $0.00840 |
| Haiku 4.5 | $0.00013 | $0.00420 |
Grade A, and why
review-proposals 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 10d 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 — 377 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Proposals
Triages improvement-proposal MCP items created by /session-retrospective when a cross-session
trend graduates. Presents pending proposals, collects a per-proposal decision, and carries out the
disposition — including applying project-scoped config changes and filing/linking GitHub issues for
global changes.
Shared GitHub conventions (issue template, scrub rule, gh guard, dedup procedure) are not
duplicated here — see
<skill-base-dir>/../session-retrospective/references/github-feedback.md for the full C2/C4/C5
contract and dedup steps referenced throughout Step 5.
Step 0 — Parse Arguments and Read Config
Parse $ARGUMENTS:
- A UUID → single-proposal mode: skip Step 1 discovery entirely: go straight to Step 2 for that one item.
--scope globalor--scope project→ filter Step 1 discovery to only that scope's query. Absent → run both discovery queries.- Neither → full discovery, both scopes.
Read the workspace .taskorchestrator/config.yaml directly (file read, not MCP) for:
project.rootId/project.name— enables the project-scoped discovery query and per-root push in Step 5. If absent, project-scoped discovery and project-scoped acceptance are unavailable — proceed with global-only discovery.retrospective.github_feedback.enabled— defaultfalseif the block or key is absent.retrospective.github_feedback.repo— defaultjpicklyk/task-orchestratorif absent.
Step 1 — Discovery
Skip this step entirely in single-proposal mode (UUID argument supplied).
Run both queries in parallel (unless --scope narrows to one):
Global:
query_items(operation="search", query="Improvement Proposals", limit=5)
Find the "Improvement Proposals" container from the result, then:
query_items(operation="overview", anchorId="<container-uuid>", includeChildren=true)
Project-scoped (only if project.rootId is known):
query_items(operation="search", tags="improvement-proposal", ancestorId="<rootId>", limit=50)
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.
- 10d ago First seen · 377 lines · 129 tokens per session scan A 4f2e0063ef7a
review-proposals is a skill published in the GitHub repository jpicklyk/task-orchestrator (206 stars, last pushed 1mo ago), licensed MIT. It adds 129 tokens to every session and 4,202 once invoked, about $0.0006 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.
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