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/talont-org/autoskillit/build-execution-mapnpx skills add TalonT-Org/AutoSkillit --skill build-execution-mapgit clone --depth 1 https://github.com/TalonT-Org/AutoSkillitWrote 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/talont-org/autoskillit/build-execution-map)<a href="https://agentmods.dev/skills/talont-org/autoskillit/build-execution-map"><img src="https://agentmods.dev/badge/skills/talont-org/autoskillit/build-execution-map.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 | $0.00018 | $0.04418 |
| Opus 5 | $0.00009 | $0.02209 |
| Sonnet 5 | $0.00004 | $0.00884 |
| Haiku 4.5 | $0.00002 | $0.00442 |
Grade A, and why
build-execution-map 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 4d 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 — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.
build-execution-map
Analyze a set of GitHub issues for dependency relationships using AI-driven pairwise assessment, then produce a structured execution map JSON artifact that partitions issues into dependency-ordered dispatch groups.
When to Use
- Before parallel dispatch of multiple issues to prevent merge conflicts
- When sous-chef receives a
parallelrequest for N ≥ 2 issues - As a standalone pre-analysis step before running an implementation campaign
Arguments
Space-separated issue numbers (required, minimum 2), plus optional flags:
--base-ref <branch>— base branch to compare against (default:main)--assess-review-approach— assess whether each issue would benefit from a review-approach research pass before implementation (default: inactive)--max-parallel <N>— maximum number of issues in any single parallel group (default:6). Groups exceeding this cap are split into sequential sub-groups of at most N issues each.
Example: 101 103 102 --base-ref main --max-parallel 4 --assess-review-approach
Critical Constraints
NEVER:
- Modify any source code files
- Create files outside
{{AUTOSKILLIT_TEMP}}/build-execution-map/directory (relative to the current working directory) - Assume issues are independent without analysis
- Launch implementation pipelines — this skill only produces the map
- Use the
execution_maporexecution_map_reporttoken names with unspaced=(always usekey = valueformat) - Override the AI's parallelism judgment with mechanical rules
- Assume issues conflict based solely on file-name overlap without reading the issue descriptions
- Run subagents in the background (
run_in_background: trueis prohibited) - Treat a medium-severity cross-assessment as grounds for deferral — only critical severity defers
- Emit has_deferred / deferred_count / dispatched_count with markdown decorators
ALWAYS:
- Use parallel subagents (up to 8) for issue fetching in Step 1
- Use
model: "sonnet"for all subagents - Write both JSON and markdown report outputs to
{{AUTOSKILLIT_TEMP}}/build-execution-map/ - Emit
execution_mapandexecution_map_reporttokens with absolute paths (use$(pwd)to resolve the working directory prefix) - Emit structured output tokens as the final lines of text output (plain text, no markdown decorators)
- Check the actual codebase when uncertain whether two issues' changes overlap
- Capture per-pair reasoning in
pairwise_assessmentsfor auditability - Anchor all output paths to the current working directory
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.
- 4d ago First seen · 400 lines · 18 tokens per session scan A 3858dec9732b
build-execution-map is a skill published in the GitHub repository TalonT-Org/AutoSkillit (5 stars, last pushed 5d ago), licensed MIT. It adds 18 tokens to every session and 4,418 once invoked, about $0.0001 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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