SKILLEMALL.ai

BC dsh-merging-stacked-prs

Use when landing a stack of dependent GitHub PRs (A ← B ← C, where each bases on the one below) onto master, merging a PR whose base is another open PR's branch, or whenever a request mentions "stacked PRs", "PR stack", "dependent PRs", or merging several related PRs in sequence. Requires every same-repository dependency chain to use GitHub's official stacked-PR feature before landing so GitHub owns stack-wide rules, CI, ordering, retargeting, and merge state.

The skillemall take

This skill teaches an AI agent to handle stacked dependent PRs in GitHub—when one pull request bases on another and you need to merge them all to master in sequence. It promises guidance on using GitHub's built-in stacked-PR mechanism so the platform itself manages ordering, CI, and merge state.

Tests show a B grade: content quality at 80, but process at 52—meaning the instruction has substance yet structure wobbles. One file, broken references. No critical errors, untested in sandbox. Runs on most platforms: Claude, Cursor, DeepSeek, and others.

Worth installing if you frequently deal with PR stacks and want the agent to avoid merge-order confusion. Catch: requires you to set up the stack in GitHub first before asking the agent for help.

deepseek-ai/deepseek-harness Agent Skills author: deepseek-ai MIT 1 file body ≈ 1 830 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Use when landing a stack of dependent GitHub PRs (A ← B ← C, where each bases on the one below) onto master, merging a PR whose base is another open PR's…

As a process C 52/100 · Has gaps — References files that are not bundled: ../../../AGENTS.md, ../../../docs/cookbook/responding-to-pr-review-on-a-stack.md

IntegrationGitHubSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
C
52/100
Has gaps
References files that are not bundled: ../../../AGENTS.md, ../../../docs/cookbook/responding-to-pr-review-on-a-stack.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../../../AGENTS.md
  • warning missing-ref reference to a missing file: ../../../docs/cookbook/responding-to-pr-review-on-a-stack.md

Process rating: all ten parameters 52/100

Will not run. References files that are not bundled: ../../../AGENTS.md, ../../../docs/cookbook/responding-to-pr-review-on-a-stack.md
  • 0Tools and files. 2 referenced file(s) missing: ../../../AGENTS.md, ../../../docs/cookbook/responding-to-pr-review-on-a-stack.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 9 mutating operations with no state check
  • 100Steps. 13 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1830 tokens

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 464: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 13 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.