Use Cocona.Docs

[moreal]

• This pull request introduces a new CLI document with Cocona.Docs

• This pull request moves the GraphQL document's path to /graphql from / (base: https://planetarium.github.io/NineChronincles.Headless).
• This pull request removes Table of contents because it was staled and it can be replaced by the GitHub's feature. And it replaces the CLI help message with a link https://planetarium.github.io/NineChronicles.Headless/cli (Preview: https://moreal.github.io/NineChronicles.Headless/cli)

After it is merged, I'll overwrite the index.html in gh-pages.

PDX-4

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• To see the specific tasks where the Asana app for GitHub is being used, see below:
  • https://app.asana.com/0/0/1205841408648935
  • https://app.asana.com/0/0/1205841408648941
  • https://app.asana.com/0/0/1205841408648939

[pull-request-quantifier-deprecated]

This PR has 145 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!

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Quantification details

Label      : Medium
Size       : +15 -130
Percentile : 49%

Total files changed: 4

Change summary by file extension:
.yaml : +9 -3
.csproj : +1 -0
.cs : +1 -0
.md : +4 -127

Change counts above are quantified counts, based on the PullRequestQuantifier customizations.

Why proper sizing of changes matters

Optimal pull request sizes drive a better predictable PR flow as they strike a
balance between between PR complexity and PR review overhead. PRs within the
optimal size (typical small, or medium sized PRs) mean:

• Fast and predictable releases to production:
  • Optimal size changes are more likely to be reviewed faster with fewer
    iterations.
  • Similarity in low PR complexity drives similar review times.
• Review quality is likely higher as complexity is lower:
  • Bugs are more likely to be detected.
  • Code inconsistencies are more likely to be detected.
• Knowledge sharing is improved within the participants:
  • Small portions can be assimilated better.
• Better engineering practices are exercised:
  • Solving big problems by dividing them in well contained, smaller problems.
  • Exercising separation of concerns within the code changes.

What can I do to optimize my changes

• Use the PullRequestQuantifier to quantify your PR accurately
  • Create a context profile for your repo using the context generator
  • Exclude files that are not necessary to be reviewed or do not increase the review complexity. Example: Autogenerated code, docs, project IDE setting files, binaries, etc. Check out the Excluded section from your prquantifier.yaml context profile.
  • Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your prquantifier.yaml context profile.
  • Only use the labels that matter to you, see context specification to customize your prquantifier.yaml context profile.
• Change your engineering behaviors
  • For PRs that fall outside of the desired spectrum, review the details and check if:
    • Your PR could be split in smaller, self-contained PRs instead
    • Your PR only solves one particular issue. (For example, don't refactor and code new features in the same PR).

How to interpret the change counts in git diff output

• One line was added: +1 -0
• One line was deleted: +0 -1
• One line was modified: +1 -1 (git diff doesn't know about modified, it will
  interpret that line like one addition plus one deletion)
• Change percentiles: Change characteristics (addition, deletion, modification)
  of this PR in relation to all other PRs within the repository.

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